Overview

Dataset statistics

Number of variables81
Number of observations23249
Missing cells68123
Missing cells (%)3.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory276.6 MiB
Average record size in memory12.2 KiB

Variable types

DateTime5
Unsupported26
Numeric23
Text15
Categorical11
URL1

Alerts

primary_root_cause_id_name is highly imbalanced (99.6%)Imbalance
alert_criteria is highly imbalanced (78.9%)Imbalance
tactic_id_name is highly imbalanced (83.4%)Imbalance
stage_id_name is highly imbalanced (60.2%)Imbalance
secondary_root_cause_id_name is highly imbalanced (99.7%)Imbalance
partner_email has 357 (1.5%) missing valuesMissing
postponed_reason has 337 (1.4%) missing valuesMissing
team_id has 350 (1.5%) missing valuesMissing
team_id_name has 350 (1.5%) missing valuesMissing
subtechnique_id has 365 (1.6%) missing valuesMissing
partner_id_name has 332 (1.4%) missing valuesMissing
solution has 286 (1.2%) missing valuesMissing
product_id has 365 (1.6%) missing valuesMissing
dragonfly_customer has 775 (3.3%) missing valuesMissing
primary_root_cause_id_name has 368 (1.6%) missing valuesMissing
subtechnique_id_name has 365 (1.6%) missing valuesMissing
tag_ids has 366 (1.6%) missing valuesMissing
description_plain has 459 (2.0%) missing valuesMissing
alert_criteria has 354 (1.5%) missing valuesMissing
product_id_name has 365 (1.6%) missing valuesMissing
active has 369 (1.6%) missing valuesMissing
cicore_id has 351 (1.5%) missing valuesMissing
ticket_type_id has 319 (1.4%) missing valuesMissing
user_id has 318 (1.4%) missing valuesMissing
tactic_id_name has 362 (1.6%) missing valuesMissing
tactic_id has 362 (1.6%) missing valuesMissing
ticket_source has 336 (1.4%) missing valuesMissing
description has 274 (1.2%) missing valuesMissing
user_id_name has 318 (1.4%) missing valuesMissing
cicore_id_name has 351 (1.5%) missing valuesMissing
partner_id has 332 (1.4%) missing valuesMissing
ticket_type_id_name has 319 (1.4%) missing valuesMissing
has_solution has 317 (1.4%) missing valuesMissing
odoo_success_state has 351 (1.5%) missing valuesMissing
cicore has 7652 (32.9%) missing valuesMissing
team has 350 (1.5%) missing valuesMissing
primary_root_cause_id has 368 (1.6%) missing valuesMissing
first_assigned_team_name has 362 (1.6%) missing valuesMissing
secondary_root_cause_id has 368 (1.6%) missing valuesMissing
secondary_root_cause_id_name has 368 (1.6%) missing valuesMissing
technique_id_name has 362 (1.6%) missing valuesMissing
technique_id has 362 (1.6%) missing valuesMissing
location has 365 (1.6%) missing valuesMissing
first_assigned_team has 362 (1.6%) missing valuesMissing
cicore_id_business_process has 23030 (99.1%) missing valuesMissing
ml_search has 23024 (99.0%) missing valuesMissing
assignment_count is highly skewed (γ1 = 38.53978418)Skewed
assign_min is highly skewed (γ1 = 23.86209616)Skewed
stage_change_count is highly skewed (γ1 = 33.31984021)Skewed
id has unique valuesUnique
name has unique valuesUnique
access_url has unique valuesUnique
partner_email is an unsupported type, check if it needs cleaning or further analysisUnsupported
postponed_reason is an unsupported type, check if it needs cleaning or further analysisUnsupported
subtechnique_id is an unsupported type, check if it needs cleaning or further analysisUnsupported
product_id is an unsupported type, check if it needs cleaning or further analysisUnsupported
tag_ids is an unsupported type, check if it needs cleaning or further analysisUnsupported
last_comming_from is an unsupported type, check if it needs cleaning or further analysisUnsupported
active is an unsupported type, check if it needs cleaning or further analysisUnsupported
cicore_id is an unsupported type, check if it needs cleaning or further analysisUnsupported
user_id is an unsupported type, check if it needs cleaning or further analysisUnsupported
ticket_class is an unsupported type, check if it needs cleaning or further analysisUnsupported
tactic_id is an unsupported type, check if it needs cleaning or further analysisUnsupported
ticket_source is an unsupported type, check if it needs cleaning or further analysisUnsupported
description is an unsupported type, check if it needs cleaning or further analysisUnsupported
ticket_type_related is an unsupported type, check if it needs cleaning or further analysisUnsupported
has_solution is an unsupported type, check if it needs cleaning or further analysisUnsupported
odoo_success_state is an unsupported type, check if it needs cleaning or further analysisUnsupported
cicore is an unsupported type, check if it needs cleaning or further analysisUnsupported
team is an unsupported type, check if it needs cleaning or further analysisUnsupported
sla_resolution_status is an unsupported type, check if it needs cleaning or further analysisUnsupported
sla_response_status is an unsupported type, check if it needs cleaning or further analysisUnsupported
primary_root_cause_id is an unsupported type, check if it needs cleaning or further analysisUnsupported
secondary_root_cause_id is an unsupported type, check if it needs cleaning or further analysisUnsupported
technique_id is an unsupported type, check if it needs cleaning or further analysisUnsupported
location is an unsupported type, check if it needs cleaning or further analysisUnsupported
cicore_id_business_process is an unsupported type, check if it needs cleaning or further analysisUnsupported
ml_search is an unsupported type, check if it needs cleaning or further analysisUnsupported
current_duration has 11194 (48.1%) zerosZeros
assignment_count has 7159 (30.8%) zerosZeros
customer_cms_record has 778 (3.3%) zerosZeros
assign_min has 14914 (64.1%) zerosZeros
ticket_type_sequence has 2383 (10.2%) zerosZeros
time_hour has 877 (3.8%) zerosZeros
commercial_partner_longitude has 18717 (80.5%) zerosZeros
commercial_partner_latitude has 18717 (80.5%) zerosZeros
team_change_count has 19658 (84.6%) zerosZeros
followers_count has 10859 (46.7%) zerosZeros
total_hours_spent has 18161 (78.1%) zerosZeros
first_assigned_team has 19599 (84.3%) zerosZeros

Reproduction

Analysis started2024-06-22 15:53:19.766689
Analysis finished2024-06-22 16:05:49.159451
Duration12 minutes and 29.39 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

Distinct15425
Distinct (%)66.3%
Missing0
Missing (%)0.0%
Memory size181.8 KiB
Minimum2024-05-23 09:59:35
Maximum2024-06-22 15:49:14
2024-06-22T10:05:49.220024image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:05:49.305680image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

partner_email
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing357
Missing (%)1.5%
Memory size1.3 MiB

current_duration
Real number (ℝ)

ZEROS 

Distinct2862
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6571868
Minimum0
Maximum416.13
Zeros11194
Zeros (%)48.1%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:49.379674image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.016666667
Q30.63333333
95-th percentile11.287333
Maximum416.13
Range416.13
Interquartile range (IQR)0.63333333

Descriptive statistics

Standard deviation12.416074
Coefficient of variation (CV)4.6726386
Kurtosis240.78018
Mean2.6571868
Median Absolute Deviation (MAD)0.016666667
Skewness12.334623
Sum61776.937
Variance154.15888
MonotonicityNot monotonic
2024-06-22T10:05:49.449558image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11194
48.1%
0.06666666667 335
 
1.4%
0.01666666667 258
 
1.1%
0.08333333333 255
 
1.1%
0.03333333333 250
 
1.1%
0.08333333333 188
 
0.8%
0.05 173
 
0.7%
0.1333333333 120
 
0.5%
0.01666666667 116
 
0.5%
9 114
 
0.5%
Other values (2852) 10246
44.1%
ValueCountFrequency (%)
0 11194
48.1%
0.01666666667 258
 
1.1%
0.01666666667 85
 
0.4%
0.01666666667 6
 
< 0.1%
0.01666666667 6
 
< 0.1%
0.01666666667 1
 
< 0.1%
0.01666666667 5
 
< 0.1%
0.01666666667 116
 
0.5%
0.01666666667 67
 
0.3%
0.03333333333 75
 
0.3%
ValueCountFrequency (%)
416.13 1
< 0.1%
402.4466667 1
< 0.1%
324.2533333 1
< 0.1%
321.4866667 1
< 0.1%
313.3533333 1
< 0.1%
305.4533333 1
< 0.1%
240.6666667 1
< 0.1%
222.79 1
< 0.1%
216.5766667 1
< 0.1%
216.1766667 1
< 0.1%

message_total_count
Real number (ℝ)

Distinct93
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.0327326
Minimum0
Maximum451
Zeros35
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:49.521533image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q14
median6
Q39
95-th percentile19
Maximum451
Range451
Interquartile range (IQR)5

Descriptive statistics

Standard deviation7.9391453
Coefficient of variation (CV)0.98834926
Kurtosis529.21826
Mean8.0327326
Median Absolute Deviation (MAD)2
Skewness14.599286
Sum186753
Variance63.030028
MonotonicityNot monotonic
2024-06-22T10:05:49.832392image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 5687
24.5%
6 3502
15.1%
8 2313
9.9%
7 2131
 
9.2%
5 2047
 
8.8%
9 1127
 
4.8%
10 778
 
3.3%
3 718
 
3.1%
11 655
 
2.8%
2 591
 
2.5%
Other values (83) 3700
15.9%
ValueCountFrequency (%)
0 35
 
0.2%
1 16
 
0.1%
2 591
 
2.5%
3 718
 
3.1%
4 5687
24.5%
5 2047
 
8.8%
6 3502
15.1%
7 2131
 
9.2%
8 2313
9.9%
9 1127
 
4.8%
ValueCountFrequency (%)
451 1
 
< 0.1%
184 1
 
< 0.1%
175 1
 
< 0.1%
174 2
< 0.1%
166 1
 
< 0.1%
163 1
 
< 0.1%
161 1
 
< 0.1%
159 3
< 0.1%
156 1
 
< 0.1%
155 1
 
< 0.1%
Distinct20292
Distinct (%)88.1%
Missing205
Missing (%)0.9%
Memory size181.8 KiB
Minimum2000-01-01 00:00:00
Maximum2024-06-22 15:49:14
2024-06-22T10:05:49.909052image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:05:49.987277image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

postponed_reason
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing337
Missing (%)1.4%
Memory size838.1 KiB

team_id
Real number (ℝ)

MISSING 

Distinct126
Distinct (%)0.6%
Missing350
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean942.38023
Minimum1
Maximum1299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:50.065149image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q11064
median1113
Q31191
95-th percentile1217
Maximum1299
Range1298
Interquartile range (IQR)127

Descriptive statistics

Standard deviation401.59521
Coefficient of variation (CV)0.42614986
Kurtosis0.58282075
Mean942.38023
Median Absolute Deviation (MAD)49
Skewness-1.4969804
Sum21579565
Variance161278.71
MonotonicityNot monotonic
2024-06-22T10:05:50.141128image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1216 3755
16.2%
1142 3357
14.4%
1085 2415
10.4%
373 1819
 
7.8%
2 1236
 
5.3%
1102 1039
 
4.5%
1111 997
 
4.3%
1155 992
 
4.3%
9 759
 
3.3%
1246 624
 
2.7%
Other values (116) 5906
25.4%
ValueCountFrequency (%)
1 24
 
0.1%
2 1236
5.3%
8 215
 
0.9%
9 759
3.3%
10 74
 
0.3%
11 57
 
0.2%
322 23
 
0.1%
328 7
 
< 0.1%
332 66
 
0.3%
347 1
 
< 0.1%
ValueCountFrequency (%)
1299 2
 
< 0.1%
1297 41
0.2%
1296 2
 
< 0.1%
1293 1
 
< 0.1%
1292 2
 
< 0.1%
1290 9
 
< 0.1%
1289 1
 
< 0.1%
1288 2
 
< 0.1%
1287 5
 
< 0.1%
1267 18
0.1%

team_id_name
Text

MISSING 

Distinct126
Distinct (%)0.6%
Missing350
Missing (%)1.5%
Memory size1.7 MiB
2024-06-22T10:05:50.273286image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length39
Median length34
Mean length20.856413
Min length6

Characters and Unicode

Total characters477591
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)0.1%

Sample

1st rowCBI - SOC
2nd rowCEC-Intel Services
3rd rowCEC-Storage
4th rowEIT-Security Operations Center
5th rowCEC-Network
ValueCountFrequency (%)
center 6461
 
10.6%
operations 6414
 
10.5%
3849
 
6.3%
cbi 3755
 
6.2%
soc 3755
 
6.2%
network 3357
 
5.5%
desk 2623
 
4.3%
services 2415
 
4.0%
cec-intel 2415
 
4.0%
it 1875
 
3.1%
Other values (163) 23944
39.3%
2024-06-22T10:05:50.505655image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 55917
 
11.7%
r 40881
 
8.6%
37964
 
7.9%
t 33384
 
7.0%
C 28294
 
5.9%
n 26468
 
5.5%
o 21997
 
4.6%
a 18891
 
4.0%
I 18687
 
3.9%
i 18586
 
3.9%
Other values (51) 176522
37.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 477591
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 55917
 
11.7%
r 40881
 
8.6%
37964
 
7.9%
t 33384
 
7.0%
C 28294
 
5.9%
n 26468
 
5.5%
o 21997
 
4.6%
a 18891
 
4.0%
I 18687
 
3.9%
i 18586
 
3.9%
Other values (51) 176522
37.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 477591
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 55917
 
11.7%
r 40881
 
8.6%
37964
 
7.9%
t 33384
 
7.0%
C 28294
 
5.9%
n 26468
 
5.5%
o 21997
 
4.6%
a 18891
 
4.0%
I 18687
 
3.9%
i 18586
 
3.9%
Other values (51) 176522
37.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 477591
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 55917
 
11.7%
r 40881
 
8.6%
37964
 
7.9%
t 33384
 
7.0%
C 28294
 
5.9%
n 26468
 
5.5%
o 21997
 
4.6%
a 18891
 
4.0%
I 18687
 
3.9%
i 18586
 
3.9%
Other values (51) 176522
37.0%

subtechnique_id
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)1.6%
Memory size732.0 KiB

assignment_count
Real number (ℝ)

SKEWED  ZEROS 

Distinct60
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1581143
Minimum0
Maximum442
Zeros7159
Zeros (%)30.8%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:50.594714image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum442
Range442
Interquartile range (IQR)1

Descriptive statistics

Standard deviation5.5570338
Coefficient of variation (CV)4.7983465
Kurtosis2155.9218
Mean1.1581143
Median Absolute Deviation (MAD)0
Skewness38.539784
Sum26925
Variance30.880625
MonotonicityNot monotonic
2024-06-22T10:05:50.667851image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 13295
57.2%
0 7159
30.8%
2 1451
 
6.2%
3 684
 
2.9%
4 190
 
0.8%
5 161
 
0.7%
6 52
 
0.2%
7 48
 
0.2%
8 43
 
0.2%
9 23
 
0.1%
Other values (50) 143
 
0.6%
ValueCountFrequency (%)
0 7159
30.8%
1 13295
57.2%
2 1451
 
6.2%
3 684
 
2.9%
4 190
 
0.8%
5 161
 
0.7%
6 52
 
0.2%
7 48
 
0.2%
8 43
 
0.2%
9 23
 
0.1%
ValueCountFrequency (%)
442 1
 
< 0.1%
172 2
< 0.1%
171 1
 
< 0.1%
169 1
 
< 0.1%
156 1
 
< 0.1%
155 1
 
< 0.1%
154 1
 
< 0.1%
153 3
< 0.1%
150 1
 
< 0.1%
148 1
 
< 0.1%
Distinct76
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
2024-06-22T10:05:50.755003image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length39
Median length8
Mean length11.614134
Min length8

Characters and Unicode

Total characters270017
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)0.1%

Sample

1st row0.0, 0.0
2nd row0.0, 0.0
3rd row0.0, 0.0
4th row0.0, 0.0
5th row0.0, 0.0
ValueCountFrequency (%)
0.0 37434
80.5%
40.841 1182
 
2.5%
74.18119999999999 1182
 
2.5%
29.7462013 1114
 
2.4%
95.55963059999999 1114
 
2.4%
42.34762 470
 
1.0%
71.07763 470
 
1.0%
29.74578 401
 
0.9%
95.55960999999999 401
 
0.9%
41.55355 327
 
0.7%
Other values (141) 2403
 
5.2%
2024-06-22T10:05:50.939798image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 80842
29.9%
. 46498
17.2%
9 39765
14.7%
, 23249
 
8.6%
23249
 
8.6%
5 8773
 
3.2%
1 7838
 
2.9%
4 7712
 
2.9%
7 7042
 
2.6%
2 5659
 
2.1%
Other values (4) 19390
 
7.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 270017
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 80842
29.9%
. 46498
17.2%
9 39765
14.7%
, 23249
 
8.6%
23249
 
8.6%
5 8773
 
3.2%
1 7838
 
2.9%
4 7712
 
2.9%
7 7042
 
2.6%
2 5659
 
2.1%
Other values (4) 19390
 
7.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 270017
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 80842
29.9%
. 46498
17.2%
9 39765
14.7%
, 23249
 
8.6%
23249
 
8.6%
5 8773
 
3.2%
1 7838
 
2.9%
4 7712
 
2.9%
7 7042
 
2.6%
2 5659
 
2.1%
Other values (4) 19390
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 270017
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 80842
29.9%
. 46498
17.2%
9 39765
14.7%
, 23249
 
8.6%
23249
 
8.6%
5 8773
 
3.2%
1 7838
 
2.9%
4 7712
 
2.9%
7 7042
 
2.6%
2 5659
 
2.1%
Other values (4) 19390
 
7.2%

partner_id_name
Text

MISSING 

Distinct2766
Distinct (%)12.1%
Missing332
Missing (%)1.4%
Memory size1.9 MiB
2024-06-22T10:05:51.164237image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length80
Median length67
Mean length30.028276
Min length3

Characters and Unicode

Total characters688158
Distinct characters89
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1553 ?
Unique (%)6.8%

Sample

1st rowNorthside Hospital (CPC CBI) ITSM Monitoring
2nd rowConverge TP ITSM Monitoring
3rd rowConverge TP ITSM Monitoring
4th rowGilson ITSM Monitoring
5th rowConverge TP ITSM Monitoring
ValueCountFrequency (%)
monitoring 15586
 
16.1%
itsm 13751
 
14.2%
converge 5679
 
5.9%
tp 5423
 
5.6%
cpc 3477
 
3.6%
cbi 3220
 
3.3%
inc 2028
 
2.1%
events 1954
 
2.0%
it 1885
 
2.0%
1673
 
1.7%
Other values (3828) 41898
43.4%
2024-06-22T10:05:51.483401image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
73672
 
10.7%
n 56287
 
8.2%
o 54205
 
7.9%
i 50709
 
7.4%
r 37589
 
5.5%
e 34288
 
5.0%
t 32686
 
4.7%
M 31986
 
4.6%
g 24230
 
3.5%
T 23262
 
3.4%
Other values (79) 269244
39.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 688158
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
73672
 
10.7%
n 56287
 
8.2%
o 54205
 
7.9%
i 50709
 
7.4%
r 37589
 
5.5%
e 34288
 
5.0%
t 32686
 
4.7%
M 31986
 
4.6%
g 24230
 
3.5%
T 23262
 
3.4%
Other values (79) 269244
39.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 688158
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
73672
 
10.7%
n 56287
 
8.2%
o 54205
 
7.9%
i 50709
 
7.4%
r 37589
 
5.5%
e 34288
 
5.0%
t 32686
 
4.7%
M 31986
 
4.6%
g 24230
 
3.5%
T 23262
 
3.4%
Other values (79) 269244
39.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 688158
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
73672
 
10.7%
n 56287
 
8.2%
o 54205
 
7.9%
i 50709
 
7.4%
r 37589
 
5.5%
e 34288
 
5.0%
t 32686
 
4.7%
M 31986
 
4.6%
g 24230
 
3.5%
T 23262
 
3.4%
Other values (79) 269244
39.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
MSO
17442 
CEC
5457 
No Team
 
350

Length

Max length7
Median length3
Mean length3.0602176
Min length3

Characters and Unicode

Total characters71147
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMSO
2nd rowCEC
3rd rowCEC
4th rowMSO
5th rowCEC

Common Values

ValueCountFrequency (%)
MSO 17442
75.0%
CEC 5457
 
23.5%
No Team 350
 
1.5%

Length

2024-06-22T10:05:51.582988image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-22T10:05:51.645414image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
mso 17442
73.9%
cec 5457
 
23.1%
no 350
 
1.5%
team 350
 
1.5%

Most occurring characters

ValueCountFrequency (%)
M 17442
24.5%
S 17442
24.5%
O 17442
24.5%
C 10914
15.3%
E 5457
 
7.7%
N 350
 
0.5%
o 350
 
0.5%
350
 
0.5%
T 350
 
0.5%
e 350
 
0.5%
Other values (2) 700
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 71147
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
M 17442
24.5%
S 17442
24.5%
O 17442
24.5%
C 10914
15.3%
E 5457
 
7.7%
N 350
 
0.5%
o 350
 
0.5%
350
 
0.5%
T 350
 
0.5%
e 350
 
0.5%
Other values (2) 700
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 71147
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
M 17442
24.5%
S 17442
24.5%
O 17442
24.5%
C 10914
15.3%
E 5457
 
7.7%
N 350
 
0.5%
o 350
 
0.5%
350
 
0.5%
T 350
 
0.5%
e 350
 
0.5%
Other values (2) 700
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 71147
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
M 17442
24.5%
S 17442
24.5%
O 17442
24.5%
C 10914
15.3%
E 5457
 
7.7%
N 350
 
0.5%
o 350
 
0.5%
350
 
0.5%
T 350
 
0.5%
e 350
 
0.5%
Other values (2) 700
 
1.0%

customer_cms_record
Real number (ℝ)

ZEROS 

Distinct160
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4545.8831
Minimum0
Maximum9012
Zeros778
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:51.711976image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q192
median5588
Q37069
95-th percentile7118
Maximum9012
Range9012
Interquartile range (IQR)6977

Descriptive statistics

Standard deviation3006.7552
Coefficient of variation (CV)0.66142378
Kurtosis-1.2189272
Mean4545.8831
Median Absolute Deviation (MAD)1490
Skewness-0.68306814
Sum1.0568724 × 108
Variance9040576.8
MonotonicityNot monotonic
2024-06-22T10:05:51.790636image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5588 6728
28.9%
7078 1943
 
8.4%
1 1893
 
8.1%
92 1580
 
6.8%
6177 846
 
3.6%
6911 786
 
3.4%
7110 785
 
3.4%
0 778
 
3.3%
8 575
 
2.5%
344 491
 
2.1%
Other values (150) 6844
29.4%
ValueCountFrequency (%)
0 778
3.3%
1 1893
8.1%
5 156
 
0.7%
6 16
 
0.1%
8 575
 
2.5%
9 328
 
1.4%
11 140
 
0.6%
79 37
 
0.2%
83 3
 
< 0.1%
86 453
 
1.9%
ValueCountFrequency (%)
9012 2
 
< 0.1%
9007 184
0.8%
9006 36
 
0.2%
8998 17
 
0.1%
8972 2
 
< 0.1%
8950 392
1.7%
8949 2
 
< 0.1%
8823 2
 
< 0.1%
8758 6
 
< 0.1%
8726 78
 
0.3%

solution
Text

MISSING 

Distinct3763
Distinct (%)16.4%
Missing286
Missing (%)1.2%
Memory size28.2 MiB
2024-06-22T10:05:51.942750image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length1374407
Median length620864
Mean length965.57858
Min length0

Characters and Unicode

Total characters22172581
Distinct characters121
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3460 ?
Unique (%)15.1%

Sample

1st row<p><br></p>
2nd row
3rd row
4th row<p><br></p>
5th row
ValueCountFrequency (%)
p><br></p 9322
 
7.0%
the 4763
 
3.6%
to 3511
 
2.7%
ticket 1986
 
1.5%
and 1866
 
1.4%
is 1666
 
1.3%
was 1600
 
1.2%
user 1432
 
1.1%
p 1319
 
1.0%
255 1183
 
0.9%
Other values (12477) 103822
78.4%
2024-06-22T10:05:52.200837image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 687349
 
3.1%
/ 427043
 
1.9%
e 415627
 
1.9%
t 403712
 
1.8%
r 398060
 
1.8%
n 379858
 
1.7%
f 378510
 
1.7%
i 372251
 
1.7%
v 371167
 
1.7%
b 366509
 
1.7%
Other values (111) 17972495
81.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 22172581
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 687349
 
3.1%
/ 427043
 
1.9%
e 415627
 
1.9%
t 403712
 
1.8%
r 398060
 
1.8%
n 379858
 
1.7%
f 378510
 
1.7%
i 372251
 
1.7%
v 371167
 
1.7%
b 366509
 
1.7%
Other values (111) 17972495
81.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 22172581
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 687349
 
3.1%
/ 427043
 
1.9%
e 415627
 
1.9%
t 403712
 
1.8%
r 398060
 
1.8%
n 379858
 
1.7%
f 378510
 
1.7%
i 372251
 
1.7%
v 371167
 
1.7%
b 366509
 
1.7%
Other values (111) 17972495
81.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 22172581
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 687349
 
3.1%
/ 427043
 
1.9%
e 415627
 
1.9%
t 403712
 
1.8%
r 398060
 
1.8%
n 379858
 
1.7%
f 378510
 
1.7%
i 372251
 
1.7%
v 371167
 
1.7%
b 366509
 
1.7%
Other values (111) 17972495
81.1%
Distinct689
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.8 MiB
2024-06-22T10:05:52.374990image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length73
Median length63
Mean length23.351241
Min length3

Characters and Unicode

Total characters542893
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique337 ?
Unique (%)1.4%

Sample

1st rowNorthside Hospital (CPC CBI) ITSM
2nd rowConverge TP
3rd rowConverge TP
4th rowGilson ITSM Monitoring
5th rowConverge TP
ValueCountFrequency (%)
itsm 11372
 
13.2%
converge 6516
 
7.6%
tp 6238
 
7.3%
cpc 3710
 
4.3%
location 3319
 
3.9%
3316
 
3.9%
cbi 3248
 
3.8%
main 2524
 
2.9%
llc 1961
 
2.3%
invacare 1915
 
2.2%
Other values (1098) 41711
48.6%
2024-06-22T10:05:52.644322image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63323
 
11.7%
o 31430
 
5.8%
e 31220
 
5.8%
n 30863
 
5.7%
a 26039
 
4.8%
C 24648
 
4.5%
T 22380
 
4.1%
I 21895
 
4.0%
i 21472
 
4.0%
r 21096
 
3.9%
Other values (67) 248527
45.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 542893
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
63323
 
11.7%
o 31430
 
5.8%
e 31220
 
5.8%
n 30863
 
5.7%
a 26039
 
4.8%
C 24648
 
4.5%
T 22380
 
4.1%
I 21895
 
4.0%
i 21472
 
4.0%
r 21096
 
3.9%
Other values (67) 248527
45.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 542893
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
63323
 
11.7%
o 31430
 
5.8%
e 31220
 
5.8%
n 30863
 
5.7%
a 26039
 
4.8%
C 24648
 
4.5%
T 22380
 
4.1%
I 21895
 
4.0%
i 21472
 
4.0%
r 21096
 
3.9%
Other values (67) 248527
45.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 542893
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
63323
 
11.7%
o 31430
 
5.8%
e 31220
 
5.8%
n 30863
 
5.7%
a 26039
 
4.8%
C 24648
 
4.5%
T 22380
 
4.1%
I 21895
 
4.0%
i 21472
 
4.0%
r 21096
 
3.9%
Other values (67) 248527
45.8%

product_id
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)1.6%
Memory size775.4 KiB

dragonfly_customer
Text

MISSING 

Distinct160
Distinct (%)0.7%
Missing775
Missing (%)3.3%
Memory size1.6 MiB
2024-06-22T10:05:52.849867image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length55
Median length43
Mean length17.610083
Min length3

Characters and Unicode

Total characters395769
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)0.2%

Sample

1st rowNorthside Hospital
2nd rowConverge TP
3rd rowConverge TP
4th rowGilson
5th rowConverge TP
ValueCountFrequency (%)
converge 6730
 
11.7%
tp 6730
 
11.7%
inc 4998
 
8.7%
invacare 1944
 
3.4%
technology 1924
 
3.3%
lummus 1893
 
3.3%
specialty 1853
 
3.2%
products 1622
 
2.8%
liquidpower 1580
 
2.7%
sun 846
 
1.5%
Other values (318) 27472
47.7%
2024-06-22T10:05:53.153344image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35118
 
8.9%
e 32855
 
8.3%
n 25701
 
6.5%
o 24789
 
6.3%
r 21051
 
5.3%
c 18738
 
4.7%
a 18142
 
4.6%
i 16229
 
4.1%
u 14622
 
3.7%
C 14162
 
3.6%
Other values (51) 174362
44.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 395769
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
35118
 
8.9%
e 32855
 
8.3%
n 25701
 
6.5%
o 24789
 
6.3%
r 21051
 
5.3%
c 18738
 
4.7%
a 18142
 
4.6%
i 16229
 
4.1%
u 14622
 
3.7%
C 14162
 
3.6%
Other values (51) 174362
44.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 395769
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
35118
 
8.9%
e 32855
 
8.3%
n 25701
 
6.5%
o 24789
 
6.3%
r 21051
 
5.3%
c 18738
 
4.7%
a 18142
 
4.6%
i 16229
 
4.1%
u 14622
 
3.7%
C 14162
 
3.6%
Other values (51) 174362
44.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 395769
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
35118
 
8.9%
e 32855
 
8.3%
n 25701
 
6.5%
o 24789
 
6.3%
r 21051
 
5.3%
c 18738
 
4.7%
a 18142
 
4.6%
i 16229
 
4.1%
u 14622
 
3.7%
C 14162
 
3.6%
Other values (51) 174362
44.1%

time_day
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Thursday
4527 
Friday
4140 
Tuesday
4084 
Monday
3694 
Wednesday
3506 
Other values (2)
3298 

Length

Max length9
Median length8
Mean length7.1552325
Min length6

Characters and Unicode

Total characters166352
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMonday
2nd rowMonday
3rd rowMonday
4th rowMonday
5th rowMonday

Common Values

ValueCountFrequency (%)
Thursday 4527
19.5%
Friday 4140
17.8%
Tuesday 4084
17.6%
Monday 3694
15.9%
Wednesday 3506
15.1%
Sunday 1697
 
7.3%
Saturday 1601
 
6.9%

Length

2024-06-22T10:05:53.242413image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-22T10:05:53.304412image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
thursday 4527
19.5%
friday 4140
17.8%
tuesday 4084
17.6%
monday 3694
15.9%
wednesday 3506
15.1%
sunday 1697
 
7.3%
saturday 1601
 
6.9%

Most occurring characters

ValueCountFrequency (%)
d 26755
16.1%
a 24850
14.9%
y 23249
14.0%
s 12117
7.3%
u 11909
7.2%
e 11096
6.7%
r 10268
 
6.2%
n 8897
 
5.3%
T 8611
 
5.2%
h 4527
 
2.7%
Other values (7) 24073
14.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 166352
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
d 26755
16.1%
a 24850
14.9%
y 23249
14.0%
s 12117
7.3%
u 11909
7.2%
e 11096
6.7%
r 10268
 
6.2%
n 8897
 
5.3%
T 8611
 
5.2%
h 4527
 
2.7%
Other values (7) 24073
14.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 166352
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
d 26755
16.1%
a 24850
14.9%
y 23249
14.0%
s 12117
7.3%
u 11909
7.2%
e 11096
6.7%
r 10268
 
6.2%
n 8897
 
5.3%
T 8611
 
5.2%
h 4527
 
2.7%
Other values (7) 24073
14.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 166352
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
d 26755
16.1%
a 24850
14.9%
y 23249
14.0%
s 12117
7.3%
u 11909
7.2%
e 11096
6.7%
r 10268
 
6.2%
n 8897
 
5.3%
T 8611
 
5.2%
h 4527
 
2.7%
Other values (7) 24073
14.5%

primary_root_cause_id_name
Categorical

IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing368
Missing (%)1.6%
Memory size1.3 MiB
22869 
3rd Party Vendor Infrastructure
 
7
Customer Infrastructure
 
4
Application
 
1

Length

Max length31
Median length0
Mean length0.013985403
Min length0

Characters and Unicode

Total characters320
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
22869
98.4%
3rd Party Vendor Infrastructure 7
 
< 0.1%
Customer Infrastructure 4
 
< 0.1%
Application 1
 
< 0.1%
(Missing) 368
 
1.6%

Length

2024-06-22T10:05:53.376495image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-22T10:05:53.430785image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
infrastructure 11
29.7%
3rd 7
18.9%
party 7
18.9%
vendor 7
18.9%
customer 4
 
10.8%
application 1
 
2.7%

Most occurring characters

ValueCountFrequency (%)
r 58
18.1%
t 34
10.6%
u 26
 
8.1%
25
 
7.8%
e 22
 
6.9%
a 19
 
5.9%
n 19
 
5.9%
s 15
 
4.7%
d 14
 
4.4%
c 12
 
3.8%
Other values (13) 76
23.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 320
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 58
18.1%
t 34
10.6%
u 26
 
8.1%
25
 
7.8%
e 22
 
6.9%
a 19
 
5.9%
n 19
 
5.9%
s 15
 
4.7%
d 14
 
4.4%
c 12
 
3.8%
Other values (13) 76
23.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 320
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 58
18.1%
t 34
10.6%
u 26
 
8.1%
25
 
7.8%
e 22
 
6.9%
a 19
 
5.9%
n 19
 
5.9%
s 15
 
4.7%
d 14
 
4.4%
c 12
 
3.8%
Other values (13) 76
23.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 320
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 58
18.1%
t 34
10.6%
u 26
 
8.1%
25
 
7.8%
e 22
 
6.9%
a 19
 
5.9%
n 19
 
5.9%
s 15
 
4.7%
d 14
 
4.4%
c 12
 
3.8%
Other values (13) 76
23.8%

id
Real number (ℝ)

UNIQUE 

Distinct23249
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean768831.59
Minimum755013
Maximum782871
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:53.725791image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum755013
5-th percentile756402.4
Q1761896
median768406
Q3775289
95-th percentile781647.6
Maximum782871
Range27858
Interquartile range (IQR)13393

Descriptive statistics

Standard deviation8138.3379
Coefficient of variation (CV)0.010585332
Kurtosis-1.1976796
Mean768831.59
Median Absolute Deviation (MAD)6694
Skewness0.058380113
Sum1.7874566 × 1010
Variance66232544
MonotonicityNot monotonic
2024-06-22T10:05:53.808036image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
782701 1
 
< 0.1%
771123 1
 
< 0.1%
771167 1
 
< 0.1%
771211 1
 
< 0.1%
771112 1
 
< 0.1%
771230 1
 
< 0.1%
771124 1
 
< 0.1%
771217 1
 
< 0.1%
771228 1
 
< 0.1%
769738 1
 
< 0.1%
Other values (23239) 23239
> 99.9%
ValueCountFrequency (%)
755013 1
< 0.1%
755014 1
< 0.1%
755015 1
< 0.1%
755016 1
< 0.1%
755017 1
< 0.1%
755018 1
< 0.1%
755019 1
< 0.1%
755020 1
< 0.1%
755021 1
< 0.1%
755022 1
< 0.1%
ValueCountFrequency (%)
782871 1
< 0.1%
782870 1
< 0.1%
782869 1
< 0.1%
782868 1
< 0.1%
782867 1
< 0.1%
782866 1
< 0.1%
782865 1
< 0.1%
782864 1
< 0.1%
782863 1
< 0.1%
782862 1
< 0.1%
Distinct21563
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size181.8 KiB
Minimum2024-05-23 09:54:38
Maximum2024-06-22 09:50:13
2024-06-22T10:05:53.891572image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:05:53.980376image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

subtechnique_id_name
Text

MISSING 

Distinct65
Distinct (%)0.3%
Missing365
Missing (%)1.6%
Memory size1.3 MiB
2024-06-22T10:05:54.118542image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length53
Median length0
Mean length0.39761405
Min length0

Characters and Unicode

Total characters9099
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.1%

Sample

1st rowWeb Protocols
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
accounts 115
 
9.2%
protocols 112
 
9.0%
web 109
 
8.8%
malicious 96
 
7.7%
file 93
 
7.5%
domain 69
 
5.5%
cloud 48
 
3.9%
memory 29
 
2.3%
powershell 28
 
2.3%
local 27
 
2.2%
Other values (93) 518
41.6%
2024-06-22T10:05:54.350832image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1066
 
11.7%
i 692
 
7.6%
c 648
 
7.1%
630
 
6.9%
l 570
 
6.3%
e 545
 
6.0%
s 529
 
5.8%
n 459
 
5.0%
t 429
 
4.7%
a 417
 
4.6%
Other values (40) 3114
34.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9099
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 1066
 
11.7%
i 692
 
7.6%
c 648
 
7.1%
630
 
6.9%
l 570
 
6.3%
e 545
 
6.0%
s 529
 
5.8%
n 459
 
5.0%
t 429
 
4.7%
a 417
 
4.6%
Other values (40) 3114
34.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9099
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 1066
 
11.7%
i 692
 
7.6%
c 648
 
7.1%
630
 
6.9%
l 570
 
6.3%
e 545
 
6.0%
s 529
 
5.8%
n 459
 
5.0%
t 429
 
4.7%
a 417
 
4.6%
Other values (40) 3114
34.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9099
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 1066
 
11.7%
i 692
 
7.6%
c 648
 
7.1%
630
 
6.9%
l 570
 
6.3%
e 545
 
6.0%
s 529
 
5.8%
n 459
 
5.0%
t 429
 
4.7%
a 417
 
4.6%
Other values (40) 3114
34.2%

tag_ids
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing366
Missing (%)1.6%
Memory size1.5 MiB

last_comming_from
Unsupported

REJECTED  UNSUPPORTED 

Missing47
Missing (%)0.2%
Memory size1.3 MiB

description_plain
Text

MISSING 

Distinct21542
Distinct (%)94.5%
Missing459
Missing (%)2.0%
Memory size33.7 MiB
2024-06-22T10:05:54.588281image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length36963
Median length4572
Mean length861.03124
Min length0

Characters and Unicode

Total characters19622902
Distinct characters445
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21238 ?
Unique (%)93.2%

Sample

1st row     [EXTERNAL SENDER] This message was sent to you automatically by Exabeam on the following high risk event by an asset. High risk session by asset: mm3he87-bfl with a risk score of 150 Asset Name: mm3he87-bfl Asset IP: 99.16.42.10 Top user for this asset: Louchion Wright, Tiffany Williams Session Start Time: June 10 2024, 12:00AM (GMT) Session End Time: June 11 2024, 12:00AM (GMT) Top Risk Reason: A security alert is associated with the asset. This is a SOC Alert for Northside Hospital Exabeam Advanced Analytics SIEM. \n     [EXTERNAL SENDER] This message was sent to you automatically by Exabeam on the following high risk event by an asset. High risk session by asset: radjht60-nfshi with a risk score of 95 Asset Name: radjht60-nfshi Asset IP: 10.47.10.173 Top user for this asset: Radiology iis Session Start Time: June 10 2024, 12:00AM (GMT) Session End Time: June 11 2024, 12:00AM (GMT) Top Risk Reason: A security alert is associated with the asset. This is the first occurrence of this security alert name on this asset This is a SOC Alert for Northside Hospital Exabeam Advanced Analytics SIEM.
2nd row Alert: Zabbix agent on cec-lex-pkirt.converge.cloud is unreachable for 10 minutes : PROBLEM for cec-lex-pkirt.converge.cloud (Q3H9A5YVD5F47B) Severity: warning Hostname: cec-lex-pkirt.converge.cloud Ip: 172.19.32.70 Name: Zabbix agent on cec-lex-pkirt.converge.cloud is unreachable for 10 minutes Severity: Average Status: PROBLEM URL: http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67711068&eventid=78195207 Integration name: Zabbix
3rd row Alert: cec-lex-v7000-c01.converge.cloud - Write Cache PC - Stat Peak > 75 : PROBLEM for 172.19.1.40 (Q0O1HK5DO9316R) Severity: warning Hostname: 172.19.1.40 Ip: 127.0.0.1 Name: cec-lex-v7000-c01.converge.cloud - Write Cache PC - Stat Peak > 75 Severity: High Status: PROBLEM URL: http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67710729&eventid=78196036 Integration name: CEC-Storage-Zabbix
4th row     [EXTERNAL SENDER] Review this incident.                                                                                                                                                                                                                                                                                        Microsoft 365 Defender has detected a security threat in your environment View incident details: ID 8621 Incident name Email messages removed after delivery​ Severity Informational Categories InitialAccess Time June 10, 2024 14:25 UTC Incident page https://security.microsoft.com/incidents/byalert?alertId=fabb54cb1b-8146-7c15-9000-08dc8957da74&source=incidentemail&tid=ca84dc0c-3fcb-4386-85ad-fbb73fbfded4 Account information Organization name Gilson Inc. Privacy Statement Microsoft Corporation, One Microsoft Way, ​Redmond, WA 98052​
5th row Alert: LEX/ORD Management IPSec Tunnel may be DOWN : PROBLEM for MSC-ORD-MGT-FW (Q1U341JUYZRGLL) Severity: warning Hostname: MSC-ORD-MGT-FW Ip: 172.18.0.19 Name: LEX/ORD Management IPSec Tunnel may be DOWN Severity: High Status: PROBLEM URL: http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67811389&eventid=78196413 Integration name: Zabbix
ValueCountFrequency (%)
96891
 
4.2%
the 54946
 
2.4%
to 36401
 
1.6%
for 28919
 
1.3%
this 25690
 
1.1%
name 24321
 
1.1%
is 23858
 
1.0%
of 23386
 
1.0%
a 20422
 
0.9%
and 18209
 
0.8%
Other values (96041) 1955954
84.7%
2024-06-22T10:05:54.919391image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2300182
 
11.7%
e 1460421
 
7.4%
t 977268
 
5.0%
881476
 
4.5%
i 872421
 
4.4%
a 828417
 
4.2%
o 827952
 
4.2%
n 798149
 
4.1%
r 751495
 
3.8%
s 729344
 
3.7%
Other values (435) 9195777
46.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19622902
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2300182
 
11.7%
e 1460421
 
7.4%
t 977268
 
5.0%
881476
 
4.5%
i 872421
 
4.4%
a 828417
 
4.2%
o 827952
 
4.2%
n 798149
 
4.1%
r 751495
 
3.8%
s 729344
 
3.7%
Other values (435) 9195777
46.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19622902
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2300182
 
11.7%
e 1460421
 
7.4%
t 977268
 
5.0%
881476
 
4.5%
i 872421
 
4.4%
a 828417
 
4.2%
o 827952
 
4.2%
n 798149
 
4.1%
r 751495
 
3.8%
s 729344
 
3.7%
Other values (435) 9195777
46.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19622902
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2300182
 
11.7%
e 1460421
 
7.4%
t 977268
 
5.0%
881476
 
4.5%
i 872421
 
4.4%
a 828417
 
4.2%
o 827952
 
4.2%
n 798149
 
4.1%
r 751495
 
3.8%
s 729344
 
3.7%
Other values (435) 9195777
46.9%

stage_id
Real number (ℝ)

Distinct45
Distinct (%)0.2%
Missing28
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean62.07799
Minimum1
Maximum563
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:55.004278image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q13
median3
Q36
95-th percentile556
Maximum563
Range562
Interquartile range (IQR)3

Descriptive statistics

Standard deviation167.72814
Coefficient of variation (CV)2.7018938
Kurtosis4.6361549
Mean62.07799
Median Absolute Deviation (MAD)0
Skewness2.5734583
Sum1441513
Variance28132.727
MonotonicityNot monotonic
2024-06-22T10:05:55.076836image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
3 14185
61.0%
6 4913
 
21.1%
556 1332
 
5.7%
29 480
 
2.1%
538 385
 
1.7%
2 260
 
1.1%
7 228
 
1.0%
562 203
 
0.9%
8 193
 
0.8%
4 172
 
0.7%
Other values (35) 870
 
3.7%
ValueCountFrequency (%)
1 96
 
0.4%
2 260
 
1.1%
3 14185
61.0%
4 172
 
0.7%
6 4913
 
21.1%
7 228
 
1.0%
8 193
 
0.8%
9 25
 
0.1%
10 56
 
0.2%
21 6
 
< 0.1%
ValueCountFrequency (%)
563 126
 
0.5%
562 203
 
0.9%
561 4
 
< 0.1%
560 2
 
< 0.1%
559 38
 
0.2%
558 55
 
0.2%
557 47
 
0.2%
556 1332
5.7%
555 40
 
0.2%
539 1
 
< 0.1%

alert_criteria
Categorical

IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing354
Missing (%)1.5%
Memory size1.5 MiB
Unclassified
21702 
False positive
 
927
True positive
 
266

Length

Max length14
Median length12
Mean length12.092597
Min length12

Characters and Unicode

Total characters276860
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnclassified
2nd rowUnclassified
3rd rowUnclassified
4th rowUnclassified
5th rowUnclassified

Common Values

ValueCountFrequency (%)
Unclassified 21702
93.3%
False positive 927
 
4.0%
True positive 266
 
1.1%
(Missing) 354
 
1.5%

Length

2024-06-22T10:05:55.148520image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-22T10:05:55.211983image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
unclassified 21702
90.1%
positive 1193
 
5.0%
false 927
 
3.8%
true 266
 
1.1%

Most occurring characters

ValueCountFrequency (%)
i 45790
16.5%
s 45524
16.4%
e 24088
8.7%
l 22629
8.2%
a 22629
8.2%
U 21702
7.8%
n 21702
7.8%
c 21702
7.8%
f 21702
7.8%
d 21702
7.8%
Other values (9) 7690
 
2.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 276860
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 45790
16.5%
s 45524
16.4%
e 24088
8.7%
l 22629
8.2%
a 22629
8.2%
U 21702
7.8%
n 21702
7.8%
c 21702
7.8%
f 21702
7.8%
d 21702
7.8%
Other values (9) 7690
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 276860
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 45790
16.5%
s 45524
16.4%
e 24088
8.7%
l 22629
8.2%
a 22629
8.2%
U 21702
7.8%
n 21702
7.8%
c 21702
7.8%
f 21702
7.8%
d 21702
7.8%
Other values (9) 7690
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 276860
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 45790
16.5%
s 45524
16.4%
e 24088
8.7%
l 22629
8.2%
a 22629
8.2%
U 21702
7.8%
n 21702
7.8%
c 21702
7.8%
f 21702
7.8%
d 21702
7.8%
Other values (9) 7690
 
2.8%

assign_min
Real number (ℝ)

SKEWED  ZEROS 

Distinct4239
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.151206
Minimum0
Maximum6982.85
Zeros14914
Zeros (%)64.1%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:55.275291image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34.05
95-th percentile77.576
Maximum6982.85
Range6982.85
Interquartile range (IQR)4.05

Descriptive statistics

Standard deviation139.77705
Coefficient of variation (CV)6.3101328
Kurtosis931.26331
Mean22.151206
Median Absolute Deviation (MAD)0
Skewness23.862096
Sum514993.39
Variance19537.624
MonotonicityNot monotonic
2024-06-22T10:05:55.353996image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14914
64.1%
0.01 186
 
0.8%
540 97
 
0.4%
0.02 39
 
0.2%
0.44 15
 
0.1%
0.71 15
 
0.1%
0.42 14
 
0.1%
1.4 14
 
0.1%
0.53 13
 
0.1%
1.69 13
 
0.1%
Other values (4229) 7929
34.1%
ValueCountFrequency (%)
0 14914
64.1%
0.01 186
 
0.8%
0.02 39
 
0.2%
0.05 1
 
< 0.1%
0.07 6
 
< 0.1%
0.08 5
 
< 0.1%
0.09 8
 
< 0.1%
0.1 3
 
< 0.1%
0.11 1
 
< 0.1%
0.12 2
 
< 0.1%
ValueCountFrequency (%)
6982.85 1
< 0.1%
6981.85 1
< 0.1%
6981.5 1
< 0.1%
4486.82 1
< 0.1%
3701.14 1
< 0.1%
3098.55 1
< 0.1%
2714.02 1
< 0.1%
2564.22 1
< 0.1%
2444.38 1
< 0.1%
2332.85 1
< 0.1%

ticket_type_sequence
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0015915
Minimum0
Maximum13
Zeros2383
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:55.422421image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q310
95-th percentile13
Maximum13
Range13
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.8026564
Coefficient of variation (CV)0.96022565
Kurtosis-1.2770375
Mean5.0015915
Median Absolute Deviation (MAD)1
Skewness0.70227654
Sum116282
Variance23.065508
MonotonicityNot monotonic
2024-06-22T10:05:55.483500image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 6906
29.7%
13 3448
14.8%
3 3182
13.7%
1 3049
13.1%
0 2383
 
10.2%
10 2359
 
10.1%
11 1603
 
6.9%
12 319
 
1.4%
ValueCountFrequency (%)
0 2383
 
10.2%
1 3049
13.1%
2 6906
29.7%
3 3182
13.7%
10 2359
 
10.1%
11 1603
 
6.9%
12 319
 
1.4%
13 3448
14.8%
ValueCountFrequency (%)
13 3448
14.8%
12 319
 
1.4%
11 1603
 
6.9%
10 2359
 
10.1%
3 3182
13.7%
2 6906
29.7%
1 3049
13.1%
0 2383
 
10.2%

product_id_name
Text

MISSING 

Distinct289
Distinct (%)1.3%
Missing365
Missing (%)1.6%
Memory size1.7 MiB
2024-06-22T10:05:55.632883image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length89
Median length76
Mean length18.018353
Min length0

Characters and Unicode

Total characters412332
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)0.4%

Sample

1st rowSOC: Escalations: NORHOS-Northside Hospital
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
11365
20.1%
alert 3923
 
6.9%
escalations 3741
 
6.6%
soc 3741
 
6.6%
auvik 3281
 
5.8%
network 1721
 
3.0%
offline 1720
 
3.0%
noc001 1705
 
3.0%
element 1705
 
3.0%
ivc-configuration 1408
 
2.5%
Other values (410) 22369
39.5%
2024-06-22T10:05:55.904364image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44867
 
10.9%
e 26087
 
6.3%
i 24019
 
5.8%
t 23284
 
5.6%
n 19604
 
4.8%
l 18343
 
4.4%
a 18130
 
4.4%
C 17476
 
4.2%
o 16620
 
4.0%
- 15308
 
3.7%
Other values (59) 188594
45.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 412332
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
44867
 
10.9%
e 26087
 
6.3%
i 24019
 
5.8%
t 23284
 
5.6%
n 19604
 
4.8%
l 18343
 
4.4%
a 18130
 
4.4%
C 17476
 
4.2%
o 16620
 
4.0%
- 15308
 
3.7%
Other values (59) 188594
45.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 412332
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
44867
 
10.9%
e 26087
 
6.3%
i 24019
 
5.8%
t 23284
 
5.6%
n 19604
 
4.8%
l 18343
 
4.4%
a 18130
 
4.4%
C 17476
 
4.2%
o 16620
 
4.0%
- 15308
 
3.7%
Other values (59) 188594
45.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 412332
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
44867
 
10.9%
e 26087
 
6.3%
i 24019
 
5.8%
t 23284
 
5.6%
n 19604
 
4.8%
l 18343
 
4.4%
a 18130
 
4.4%
C 17476
 
4.2%
o 16620
 
4.0%
- 15308
 
3.7%
Other values (59) 188594
45.7%

active
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing369
Missing (%)1.6%
Memory size1.3 MiB
Distinct161
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.6 MiB
2024-06-22T10:05:56.113401image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length55
Median length43
Mean length17.021764
Min length0

Characters and Unicode

Total characters395739
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)0.2%

Sample

1st rowNorthside Hospital
2nd rowConverge TP
3rd rowConverge TP
4th rowGilson
5th rowConverge TP
ValueCountFrequency (%)
converge 6728
 
11.7%
tp 6728
 
11.7%
inc 4998
 
8.7%
invacare 1943
 
3.4%
technology 1924
 
3.3%
lummus 1893
 
3.3%
specialty 1853
 
3.2%
products 1622
 
2.8%
liquidpower 1580
 
2.7%
sun 846
 
1.5%
Other values (318) 27472
47.7%
2024-06-22T10:05:56.411137image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35116
 
8.9%
e 32850
 
8.3%
n 25698
 
6.5%
o 24787
 
6.3%
r 21048
 
5.3%
c 18737
 
4.7%
a 18140
 
4.6%
i 16229
 
4.1%
u 14622
 
3.7%
C 14160
 
3.6%
Other values (51) 174352
44.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 395739
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
35116
 
8.9%
e 32850
 
8.3%
n 25698
 
6.5%
o 24787
 
6.3%
r 21048
 
5.3%
c 18737
 
4.7%
a 18140
 
4.6%
i 16229
 
4.1%
u 14622
 
3.7%
C 14160
 
3.6%
Other values (51) 174352
44.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 395739
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
35116
 
8.9%
e 32850
 
8.3%
n 25698
 
6.5%
o 24787
 
6.3%
r 21048
 
5.3%
c 18737
 
4.7%
a 18140
 
4.6%
i 16229
 
4.1%
u 14622
 
3.7%
C 14160
 
3.6%
Other values (51) 174352
44.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 395739
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
35116
 
8.9%
e 32850
 
8.3%
n 25698
 
6.5%
o 24787
 
6.3%
r 21048
 
5.3%
c 18737
 
4.7%
a 18140
 
4.6%
i 16229
 
4.1%
u 14622
 
3.7%
C 14160
 
3.6%
Other values (51) 174352
44.1%

cicore_id
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing351
Missing (%)1.5%
Memory size788.6 KiB

date_tz
Real number (ℝ)

Distinct21563
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7177793 × 1012
Minimum1.7164581 × 1012
Maximum1.7190498 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:56.503122image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1.7164581 × 1012
5-th percentile1.7165693 × 1012
Q11.7171076 × 1012
median1.7177382 × 1012
Q31.71837 × 1012
95-th percentile1.7189395 × 1012
Maximum1.7190498 × 1012
Range2.591735 × 109
Interquartile range (IQR)1.262398 × 109

Descriptive statistics

Standard deviation7.4982503 × 108
Coefficient of variation (CV)0.00043650837
Kurtosis-1.1758334
Mean1.7177793 × 1012
Median Absolute Deviation (MAD)6.30677 × 108
Skewness-0.0042016975
Sum3.993665 × 1016
Variance5.6223757 × 1017
MonotonicityNot monotonic
2024-06-22T10:05:56.587344image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.717977909 × 101238
 
0.2%
1.718936298 × 101227
 
0.1%
1.71837733 × 101222
 
0.1%
1.716768313 × 101221
 
0.1%
1.718582709 × 101217
 
0.1%
1.716912851 × 101216
 
0.1%
1.717373105 × 101215
 
0.1%
1.716903295 × 101214
 
0.1%
1.716796016 × 101214
 
0.1%
1.719006792 × 101214
 
0.1%
Other values (21553) 23051
99.1%
ValueCountFrequency (%)
1.716458078 × 10121
< 0.1%
1.716458288 × 10121
< 0.1%
1.716458549 × 10121
< 0.1%
1.716458633 × 10121
< 0.1%
1.716458641 × 10121
< 0.1%
1.716458648 × 10121
< 0.1%
1.716458666 × 10121
< 0.1%
1.716458687 × 10121
< 0.1%
1.716458692 × 10121
< 0.1%
1.716459012 × 10121
< 0.1%
ValueCountFrequency (%)
1.719049813 × 10121
 
< 0.1%
1.719049782 × 10121
 
< 0.1%
1.719049439 × 10121
 
< 0.1%
1.719049421 × 10121
 
< 0.1%
1.719049379 × 10121
 
< 0.1%
1.719048764 × 10121
 
< 0.1%
1.719048468 × 10121
 
< 0.1%
1.719048305 × 10123
< 0.1%
1.719047742 × 10121
 
< 0.1%
1.719047672 × 10121
 
< 0.1%

ticket_type_id
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)0.1%
Missing319
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean5.1549498
Minimum0
Maximum11
Zeros64
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:56.867490image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q14
median5
Q36
95-th percentile10
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.3625775
Coefficient of variation (CV)0.45831242
Kurtosis-0.26701125
Mean5.1549498
Median Absolute Deviation (MAD)1
Skewness0.66274274
Sum118203
Variance5.5817726
MonotonicityNot monotonic
2024-06-22T10:05:56.930287image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5 6906
29.7%
2 3201
13.8%
6 3182
13.7%
4 3049
13.1%
3 2383
 
10.2%
9 2359
 
10.1%
10 1603
 
6.9%
11 105
 
0.5%
0 64
 
0.3%
8 28
 
0.1%
Other values (2) 50
 
0.2%
(Missing) 319
 
1.4%
ValueCountFrequency (%)
0 64
 
0.3%
1 26
 
0.1%
2 3201
13.8%
3 2383
 
10.2%
4 3049
13.1%
5 6906
29.7%
6 3182
13.7%
7 24
 
0.1%
8 28
 
0.1%
9 2359
 
10.1%
ValueCountFrequency (%)
11 105
 
0.5%
10 1603
 
6.9%
9 2359
 
10.1%
8 28
 
0.1%
7 24
 
0.1%
6 3182
13.7%
5 6906
29.7%
4 3049
13.1%
3 2383
 
10.2%
2 3201
13.8%

user_id
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing318
Missing (%)1.4%
Memory size793.7 KiB

tactic_id_name
Categorical

IMBALANCE  MISSING 

Distinct15
Distinct (%)0.1%
Missing362
Missing (%)1.6%
Memory size1.3 MiB
21101 
Initial Access
 
448
Command and Control
 
253
Execution
 
246
Credential Access
 
209
Other values (10)
 
630

Length

Max length20
Median length0
Mean length1.1040329
Min length0

Characters and Unicode

Total characters25268
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCommand and Control
2nd row
3rd row
4th rowInitial Access
5th row

Common Values

ValueCountFrequency (%)
21101
90.8%
Initial Access 448
 
1.9%
Command and Control 253
 
1.1%
Execution 246
 
1.1%
Credential Access 209
 
0.9%
Persistence 122
 
0.5%
Exfiltration 121
 
0.5%
Defense Evasion 114
 
0.5%
Lateral Movement 66
 
0.3%
Privilege Escalation 57
 
0.2%
Other values (5) 150
 
0.6%
(Missing) 362
 
1.6%

Length

2024-06-22T10:05:57.006106image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
access 657
20.5%
initial 448
14.0%
command 253
 
7.9%
and 253
 
7.9%
control 253
 
7.9%
execution 246
 
7.7%
credential 209
 
6.5%
persistence 122
 
3.8%
exfiltration 121
 
3.8%
defense 114
 
3.6%
Other values (11) 526
16.4%

Most occurring characters

ValueCountFrequency (%)
e 2582
 
10.2%
n 2441
 
9.7%
i 2107
 
8.3%
s 2013
 
8.0%
c 1943
 
7.7%
a 1779
 
7.0%
t 1759
 
7.0%
o 1509
 
6.0%
1416
 
5.6%
l 1241
 
4.9%
Other values (19) 6478
25.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 25268
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2582
 
10.2%
n 2441
 
9.7%
i 2107
 
8.3%
s 2013
 
8.0%
c 1943
 
7.7%
a 1779
 
7.0%
t 1759
 
7.0%
o 1509
 
6.0%
1416
 
5.6%
l 1241
 
4.9%
Other values (19) 6478
25.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 25268
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2582
 
10.2%
n 2441
 
9.7%
i 2107
 
8.3%
s 2013
 
8.0%
c 1943
 
7.7%
a 1779
 
7.0%
t 1759
 
7.0%
o 1509
 
6.0%
1416
 
5.6%
l 1241
 
4.9%
Other values (19) 6478
25.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 25268
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2582
 
10.2%
n 2441
 
9.7%
i 2107
 
8.3%
s 2013
 
8.0%
c 1943
 
7.7%
a 1779
 
7.0%
t 1759
 
7.0%
o 1509
 
6.0%
1416
 
5.6%
l 1241
 
4.9%
Other values (19) 6478
25.6%

name
Text

UNIQUE 

Distinct23249
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.6 MiB
2024-06-22T10:05:57.134349image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length520
Median length255
Mean length102.9449
Min length13

Characters and Unicode

Total characters2393366
Distinct characters136
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23249 ?
Unique (%)100.0%

Sample

1st rowAlert | Northside Hospital | Northside Hospital Email | NSH VECTRA ALERT (#771123)
2nd rowAlert: PD - Zabbix | ConvergeTP | Zabbix agent on cec-lex-pkirt.converge.cloud is unreachable for 10 minutes : PROBLEM for cec-lex-pkirt.converge.cloud (#771167)
3rd rowAlert: PD - CEC-Storage-Zabbix | ConvergeTP | cec-lex-v7000-c01.converge.cloud - Write Cache PC - Stat Peak > 75 : PROBLEM for 172.19.1.40 (#771211)
4th rowAlert: Email | gilson | Microsoft 365 Defender has detected a security threat (#771112)
5th rowAlert: PD - Zabbix | ConvergeTP | LEX/ORD Management IPSec Tunnel may be DOWN : PROBLEM for MSC-ORD-MGT-FW (#771230)
ValueCountFrequency (%)
68002
 
19.0%
alert 16315
 
4.6%
for 6746
 
1.9%
convergetp 5392
 
1.5%
pd 5290
 
1.5%
problem 4063
 
1.1%
auvik 4004
 
1.1%
zabbix 3737
 
1.0%
on 3713
 
1.0%
email 3712
 
1.0%
Other values (35676) 236292
66.1%
2024-06-22T10:05:57.365740image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
335753
 
14.0%
e 155291
 
6.5%
t 97160
 
4.1%
r 91220
 
3.8%
n 88993
 
3.7%
o 88392
 
3.7%
i 87940
 
3.7%
a 78031
 
3.3%
l 71562
 
3.0%
s 59861
 
2.5%
Other values (126) 1239163
51.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2393366
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
335753
 
14.0%
e 155291
 
6.5%
t 97160
 
4.1%
r 91220
 
3.8%
n 88993
 
3.7%
o 88392
 
3.7%
i 87940
 
3.7%
a 78031
 
3.3%
l 71562
 
3.0%
s 59861
 
2.5%
Other values (126) 1239163
51.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2393366
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
335753
 
14.0%
e 155291
 
6.5%
t 97160
 
4.1%
r 91220
 
3.8%
n 88993
 
3.7%
o 88392
 
3.7%
i 87940
 
3.7%
a 78031
 
3.3%
l 71562
 
3.0%
s 59861
 
2.5%
Other values (126) 1239163
51.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2393366
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
335753
 
14.0%
e 155291
 
6.5%
t 97160
 
4.1%
r 91220
 
3.8%
n 88993
 
3.7%
o 88392
 
3.7%
i 87940
 
3.7%
a 78031
 
3.3%
l 71562
 
3.0%
s 59861
 
2.5%
Other values (126) 1239163
51.8%

time_hour
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.386468
Minimum0
Maximum23
Zeros877
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:57.443657image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median13
Q318
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.5350404
Coefficient of variation (CV)0.52759513
Kurtosis-1.0098316
Mean12.386468
Median Absolute Deviation (MAD)5
Skewness-0.26708677
Sum287973
Variance42.706753
MonotonicityNot monotonic
2024-06-22T10:05:57.509709image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
14 1589
 
6.8%
15 1522
 
6.5%
13 1256
 
5.4%
18 1216
 
5.2%
19 1198
 
5.2%
16 1195
 
5.1%
17 1142
 
4.9%
20 1101
 
4.7%
12 1053
 
4.5%
21 969
 
4.2%
Other values (14) 11008
47.3%
ValueCountFrequency (%)
0 877
3.8%
1 566
2.4%
2 830
3.6%
3 724
3.1%
4 659
2.8%
5 927
4.0%
6 925
4.0%
7 842
3.6%
8 683
2.9%
9 758
3.3%
ValueCountFrequency (%)
23 817
3.5%
22 772
3.3%
21 969
4.2%
20 1101
4.7%
19 1198
5.2%
18 1216
5.2%
17 1142
4.9%
16 1195
5.1%
15 1522
6.5%
14 1589
6.8%

ticket_class
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.4 MiB

stage_sequence
Real number (ℝ)

Distinct10
Distinct (%)< 0.1%
Missing33
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean6.0979928
Minimum0
Maximum8
Zeros164
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:57.568661image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q16
median6
Q37
95-th percentile7
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.162077
Coefficient of variation (CV)0.19056713
Kurtosis12.016969
Mean6.0979928
Median Absolute Deviation (MAD)0
Skewness-3.1801889
Sum141571
Variance1.3504229
MonotonicityNot monotonic
2024-06-22T10:05:57.629999image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
6 14568
62.7%
7 7145
30.7%
1 428
 
1.8%
2 342
 
1.5%
4 228
 
1.0%
8 179
 
0.8%
0 164
 
0.7%
5 113
 
0.5%
3 41
 
0.2%
0.5 8
 
< 0.1%
(Missing) 33
 
0.1%
ValueCountFrequency (%)
0 164
 
0.7%
0.5 8
 
< 0.1%
1 428
 
1.8%
2 342
 
1.5%
3 41
 
0.2%
4 228
 
1.0%
5 113
 
0.5%
6 14568
62.7%
7 7145
30.7%
8 179
 
0.8%
ValueCountFrequency (%)
8 179
 
0.8%
7 7145
30.7%
6 14568
62.7%
5 113
 
0.5%
4 228
 
1.0%
3 41
 
0.2%
2 342
 
1.5%
1 428
 
1.8%
0.5 8
 
< 0.1%
0 164
 
0.7%

tactic_id
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing362
Missing (%)1.6%
Memory size736.3 KiB

ticket_source
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing336
Missing (%)1.4%
Memory size1.4 MiB

description
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing274
Missing (%)1.2%
Memory size128.3 MiB

commercial_partner_longitude
Real number (ℝ)

ZEROS 

Distinct76
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-14.327554
Minimum-157.8988
Maximum126.97829
Zeros18717
Zeros (%)80.5%
Negative4162
Negative (%)17.9%
Memory size181.8 KiB
2024-06-22T10:05:57.702543image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-157.8988
5-th percentile-95.559631
Q10
median0
Q30
95-th percentile0
Maximum126.97829
Range284.87709
Interquartile range (IQR)0

Descriptive statistics

Standard deviation34.864292
Coefficient of variation (CV)-2.4333737
Kurtosis1.3550928
Mean-14.327554
Median Absolute Deviation (MAD)0
Skewness-1.3773673
Sum-333101.29
Variance1215.5188
MonotonicityNot monotonic
2024-06-22T10:05:57.777060image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18717
80.5%
-74.1812 1182
 
5.1%
-95.5596306 1114
 
4.8%
-71.07763 470
 
2.0%
-95.55961 401
 
1.7%
-81.59339 327
 
1.4%
77.0027 303
 
1.3%
-107.991707 141
 
0.6%
-95.3677 133
 
0.6%
-95.04635 95
 
0.4%
Other values (66) 366
 
1.6%
ValueCountFrequency (%)
-157.8988012 1
 
< 0.1%
-157.8988 1
 
< 0.1%
-122.79884 1
 
< 0.1%
-122.39738 1
 
< 0.1%
-122.39515 6
 
< 0.1%
-122.39474 17
0.1%
-119.24289 1
 
< 0.1%
-118.60255 1
 
< 0.1%
-118.41033 1
 
< 0.1%
-118.36195 3
 
< 0.1%
ValueCountFrequency (%)
126.97829 1
 
< 0.1%
77.0027 303
 
1.3%
8.49367 48
 
0.2%
4.33685 18
 
0.1%
0 18717
80.5%
-71.07763 470
 
2.0%
-71.08865 2
 
< 0.1%
-71.79941 1
 
< 0.1%
-73.91003 58
 
0.2%
-73.98071 1
 
< 0.1%

user_id_name
Text

MISSING 

Distinct292
Distinct (%)1.3%
Missing318
Missing (%)1.4%
Memory size1.5 MiB
2024-06-22T10:05:57.957692image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length25
Median length22
Mean length12.36684
Min length0

Characters and Unicode

Total characters283584
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)0.1%

Sample

1st rowNaiman, Alex
2nd row
3rd rowSoriano, Azael_EIT
4th rowOliver, Daniel
5th rowBravo, Fernando_EIT
ValueCountFrequency (%)
exactlyit 1034
 
2.9%
bot 1034
 
2.9%
system 1034
 
2.9%
mario_eit 643
 
1.8%
martinez 643
 
1.8%
garcia 573
 
1.6%
jose_eit 545
 
1.6%
gonzalez 538
 
1.5%
daniel_eit 527
 
1.5%
aquino 517
 
1.5%
Other values (470) 27997
79.8%
2024-06-22T10:05:58.217812image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 24252
 
8.6%
e 20103
 
7.1%
18148
 
6.4%
, 15868
 
5.6%
o 14925
 
5.3%
n 14481
 
5.1%
r 13959
 
4.9%
i 13834
 
4.9%
l 13764
 
4.9%
T 10810
 
3.8%
Other values (46) 123440
43.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 283584
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 24252
 
8.6%
e 20103
 
7.1%
18148
 
6.4%
, 15868
 
5.6%
o 14925
 
5.3%
n 14481
 
5.1%
r 13959
 
4.9%
i 13834
 
4.9%
l 13764
 
4.9%
T 10810
 
3.8%
Other values (46) 123440
43.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 283584
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 24252
 
8.6%
e 20103
 
7.1%
18148
 
6.4%
, 15868
 
5.6%
o 14925
 
5.3%
n 14481
 
5.1%
r 13959
 
4.9%
i 13834
 
4.9%
l 13764
 
4.9%
T 10810
 
3.8%
Other values (46) 123440
43.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 283584
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 24252
 
8.6%
e 20103
 
7.1%
18148
 
6.4%
, 15868
 
5.6%
o 14925
 
5.3%
n 14481
 
5.1%
r 13959
 
4.9%
i 13834
 
4.9%
l 13764
 
4.9%
T 10810
 
3.8%
Other values (46) 123440
43.5%
Distinct19726
Distinct (%)85.4%
Missing160
Missing (%)0.7%
Memory size181.8 KiB
Minimum2000-01-01 00:00:00
Maximum2024-06-22 15:49:16
2024-06-22T10:05:58.301694image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:05:58.378614image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

cicore_id_name
Text

MISSING 

Distinct1314
Distinct (%)5.7%
Missing351
Missing (%)1.5%
Memory size1.6 MiB
2024-06-22T10:05:58.518471image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length151
Median length63
Mean length15.147567
Min length0

Characters and Unicode

Total characters346849
Distinct characters75
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique515 ?
Unique (%)2.2%

Sample

1st rowSOC Incident Management Northside Hospital
2nd rowCEC-ITSM Processes
3rd rowCEC-ITSM Processes
4th row
5th rowmsc-ord-mgt-fw01
ValueCountFrequency (%)
management 3835
 
9.4%
incident 3745
 
9.2%
soc 3741
 
9.2%
2404
 
5.9%
processes 2195
 
5.4%
cec-itsm 2195
 
5.4%
ivc 1729
 
4.3%
edelman 782
 
1.9%
austin.docreit.com 704
 
1.7%
other 573
 
1.4%
Other values (1515) 18697
46.1%
2024-06-22T10:05:58.751718image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 27843
 
8.0%
25018
 
7.2%
n 21496
 
6.2%
t 17685
 
5.1%
C 15829
 
4.6%
- 14717
 
4.2%
a 14423
 
4.2%
i 12683
 
3.7%
s 12427
 
3.6%
S 12355
 
3.6%
Other values (65) 172373
49.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 346849
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 27843
 
8.0%
25018
 
7.2%
n 21496
 
6.2%
t 17685
 
5.1%
C 15829
 
4.6%
- 14717
 
4.2%
a 14423
 
4.2%
i 12683
 
3.7%
s 12427
 
3.6%
S 12355
 
3.6%
Other values (65) 172373
49.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 346849
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 27843
 
8.0%
25018
 
7.2%
n 21496
 
6.2%
t 17685
 
5.1%
C 15829
 
4.6%
- 14717
 
4.2%
a 14423
 
4.2%
i 12683
 
3.7%
s 12427
 
3.6%
S 12355
 
3.6%
Other values (65) 172373
49.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 346849
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 27843
 
8.0%
25018
 
7.2%
n 21496
 
6.2%
t 17685
 
5.1%
C 15829
 
4.6%
- 14717
 
4.2%
a 14423
 
4.2%
i 12683
 
3.7%
s 12427
 
3.6%
S 12355
 
3.6%
Other values (65) 172373
49.7%
Distinct15237
Distinct (%)66.0%
Missing176
Missing (%)0.8%
Memory size181.8 KiB
Minimum2000-01-01 00:00:00
Maximum2024-06-22 15:48:07
2024-06-22T10:05:58.833776image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:05:58.911358image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

partner_id
Real number (ℝ)

MISSING 

Distinct2770
Distinct (%)12.1%
Missing332
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean37495.251
Minimum8
Maximum104344
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:58.986300image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile3873
Q129834
median35003
Q351510
95-th percentile75781
Maximum104344
Range104336
Interquartile range (IQR)21676

Descriptive statistics

Standard deviation22657.786
Coefficient of variation (CV)0.60428414
Kurtosis0.11557839
Mean37495.251
Median Absolute Deviation (MAD)16489
Skewness0.40689172
Sum8.5927867 × 108
Variance5.1337525 × 108
MonotonicityNot monotonic
2024-06-22T10:05:59.061851image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29834 5282
22.7%
6298 1097
 
4.7%
3873 960
 
4.1%
37343 828
 
3.6%
44607 785
 
3.4%
51492 783
 
3.4%
51540 480
 
2.1%
41039 420
 
1.8%
51475 416
 
1.8%
75781 390
 
1.7%
Other values (2760) 11476
49.4%
ValueCountFrequency (%)
8 3
 
< 0.1%
22 2
 
< 0.1%
78 11
< 0.1%
102 1
 
< 0.1%
110 5
< 0.1%
111 1
 
< 0.1%
113 12
0.1%
115 12
0.1%
116 1
 
< 0.1%
118 3
 
< 0.1%
ValueCountFrequency (%)
104344 1
< 0.1%
104333 1
< 0.1%
104326 1
< 0.1%
104325 1
< 0.1%
104311 1
< 0.1%
104309 1
< 0.1%
104306 1
< 0.1%
104278 1
< 0.1%
104263 1
< 0.1%
104248 1
< 0.1%

ticket_type_related
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.4 MiB

ticket_type_id_name
Categorical

MISSING 

Distinct12
Distinct (%)0.1%
Missing319
Missing (%)1.4%
Memory size1.7 MiB
Incident Normal (P3)
6906 
Undefined
3201 
Incident Low (P4)
3182 
Incident High (P2)
3049 
Incident Critical (P1)
2383 
Other values (7)
4209 

Length

Max length22
Median length20
Mean length17.964937
Min length0

Characters and Unicode

Total characters411936
Distinct characters39
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUndefined
2nd rowIncident Normal (P3)
3rd rowIncident Normal (P3)
4th rowIncident Normal (P3)
5th rowIncident High (P2)

Common Values

ValueCountFrequency (%)
Incident Normal (P3) 6906
29.7%
Undefined 3201
13.8%
Incident Low (P4) 3182
13.7%
Incident High (P2) 3049
13.1%
Incident Critical (P1) 2383
 
10.2%
Service Request Normal 2359
 
10.1%
Service Request Low 1603
 
6.9%
Change 105
 
0.5%
64
 
0.3%
Problem 28
 
0.1%
Other values (2) 50
 
0.2%
(Missing) 319
 
1.4%

Length

2024-06-22T10:05:59.131562image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
incident 15520
25.1%
normal 9265
15.0%
p3 6906
11.2%
low 4785
 
7.7%
service 3962
 
6.4%
request 3962
 
6.4%
undefined 3201
 
5.2%
p4 3182
 
5.1%
p2 3049
 
4.9%
high 3049
 
4.9%
Other values (6) 4949
 
8.0%

Most occurring characters

ValueCountFrequency (%)
38964
 
9.5%
e 37953
 
9.2%
n 37573
 
9.1%
i 30548
 
7.4%
d 21922
 
5.3%
t 21915
 
5.3%
c 21889
 
5.3%
r 15638
 
3.8%
P 15548
 
3.8%
I 15520
 
3.8%
Other values (29) 154466
37.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 411936
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
38964
 
9.5%
e 37953
 
9.2%
n 37573
 
9.1%
i 30548
 
7.4%
d 21922
 
5.3%
t 21915
 
5.3%
c 21889
 
5.3%
r 15638
 
3.8%
P 15548
 
3.8%
I 15520
 
3.8%
Other values (29) 154466
37.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 411936
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
38964
 
9.5%
e 37953
 
9.2%
n 37573
 
9.1%
i 30548
 
7.4%
d 21922
 
5.3%
t 21915
 
5.3%
c 21889
 
5.3%
r 15638
 
3.8%
P 15548
 
3.8%
I 15520
 
3.8%
Other values (29) 154466
37.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 411936
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
38964
 
9.5%
e 37953
 
9.2%
n 37573
 
9.1%
i 30548
 
7.4%
d 21922
 
5.3%
t 21915
 
5.3%
c 21889
 
5.3%
r 15638
 
3.8%
P 15548
 
3.8%
I 15520
 
3.8%
Other values (29) 154466
37.5%

stage_change_count
Real number (ℝ)

SKEWED 

Distinct62
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7785281
Minimum0
Maximum442
Zeros164
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:59.196150image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile7
Maximum442
Range442
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.8147986
Coefficient of variation (CV)2.0927622
Kurtosis1768.4623
Mean2.7785281
Median Absolute Deviation (MAD)1
Skewness33.31984
Sum64598
Variance33.811882
MonotonicityNot monotonic
2024-06-22T10:05:59.266086image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 8964
38.6%
1 6216
26.7%
3 4241
18.2%
4 1273
 
5.5%
5 776
 
3.3%
6 407
 
1.8%
7 319
 
1.4%
8 224
 
1.0%
0 164
 
0.7%
9 157
 
0.7%
Other values (52) 508
 
2.2%
ValueCountFrequency (%)
0 164
 
0.7%
1 6216
26.7%
2 8964
38.6%
3 4241
18.2%
4 1273
 
5.5%
5 776
 
3.3%
6 407
 
1.8%
7 319
 
1.4%
8 224
 
1.0%
9 157
 
0.7%
ValueCountFrequency (%)
442 1
 
< 0.1%
175 1
 
< 0.1%
171 1
 
< 0.1%
170 1
 
< 0.1%
169 1
 
< 0.1%
157 1
 
< 0.1%
155 4
< 0.1%
153 1
 
< 0.1%
150 1
 
< 0.1%
148 2
< 0.1%

commercial_partner_id
Real number (ℝ)

Distinct689
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33090.434
Minimum1
Maximum104344
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:59.337665image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile426
Q117442
median29361
Q351490
95-th percentile65887
Maximum104344
Range104343
Interquartile range (IQR)34048

Descriptive statistics

Standard deviation21132.167
Coefficient of variation (CV)0.63861861
Kurtosis-0.26576456
Mean33090.434
Median Absolute Deviation (MAD)22112
Skewness0.15767099
Sum7.693195 × 108
Variance4.4656849 × 108
MonotonicityNot monotonic
2024-06-22T10:05:59.599206image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27469 5313
22.9%
426 1182
 
5.1%
5995 1114
 
4.8%
52975 889
 
3.8%
37319 834
 
3.6%
44606 786
 
3.4%
51490 785
 
3.4%
29361 648
 
2.8%
51538 483
 
2.1%
17442 470
 
2.0%
Other values (679) 10745
46.2%
ValueCountFrequency (%)
1 355
 
1.5%
23 384
 
1.7%
39 9
 
< 0.1%
66 1
 
< 0.1%
426 1182
5.1%
436 327
 
1.4%
2778 48
 
0.2%
2792 303
 
1.3%
2793 133
 
0.6%
2799 95
 
0.4%
ValueCountFrequency (%)
104344 1
 
< 0.1%
104326 1
 
< 0.1%
102243 3
< 0.1%
102184 1
 
< 0.1%
102182 2
< 0.1%
102071 1
 
< 0.1%
102062 1
 
< 0.1%
101957 1
 
< 0.1%
101912 1
 
< 0.1%
101772 4
< 0.1%

commercial_partner_latitude
Real number (ℝ)

ZEROS 

Distinct76
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1133727
Minimum0
Maximum61.066692
Zeros18717
Zeros (%)80.5%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:59.673568image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile40.841
Maximum61.066692
Range61.066692
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.822722
Coefficient of variation (CV)2.0837826
Kurtosis1.4446457
Mean7.1133727
Median Absolute Deviation (MAD)0
Skewness1.7429878
Sum165378.8
Variance219.71309
MonotonicityNot monotonic
2024-06-22T10:05:59.750625image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18717
80.5%
40.841 1182
 
5.1%
29.7462013 1114
 
4.8%
42.34762 470
 
2.0%
29.74578 401
 
1.7%
41.55355 327
 
1.4%
28.42826 303
 
1.3%
61.0666922 141
 
0.6%
29.75894 133
 
0.6%
29.63178 95
 
0.4%
Other values (66) 366
 
1.6%
ValueCountFrequency (%)
0 18717
80.5%
21.3338914 1
 
< 0.1%
21.33427 1
 
< 0.1%
28.42826 303
 
1.3%
29.63178 95
 
0.4%
29.66724 5
 
< 0.1%
29.74578 401
 
1.7%
29.7462 8
 
< 0.1%
29.7462013 1114
 
4.8%
29.75894 133
 
0.6%
ValueCountFrequency (%)
61.0666922 141
0.6%
52.07758 18
 
0.1%
49.47548 48
 
0.2%
45.19963 4
 
< 0.1%
44.94975 2
 
< 0.1%
43.75466 4
 
< 0.1%
42.58139 1
 
< 0.1%
42.55047 1
 
< 0.1%
42.49725 4
 
< 0.1%
42.36657 1
 
< 0.1%

team_change_count
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.18891135
Minimum0
Maximum7
Zeros19658
Zeros (%)84.6%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:05:59.813347image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.50446652
Coefficient of variation (CV)2.6703875
Kurtosis21.561481
Mean0.18891135
Median Absolute Deviation (MAD)0
Skewness3.7738226
Sum4392
Variance0.25448647
MonotonicityNot monotonic
2024-06-22T10:05:59.872059image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 19658
84.6%
1 3044
 
13.1%
2 375
 
1.6%
3 118
 
0.5%
4 35
 
0.2%
5 13
 
0.1%
6 3
 
< 0.1%
7 3
 
< 0.1%
ValueCountFrequency (%)
0 19658
84.6%
1 3044
 
13.1%
2 375
 
1.6%
3 118
 
0.5%
4 35
 
0.2%
5 13
 
0.1%
6 3
 
< 0.1%
7 3
 
< 0.1%
ValueCountFrequency (%)
7 3
 
< 0.1%
6 3
 
< 0.1%
5 13
 
0.1%
4 35
 
0.2%
3 118
 
0.5%
2 375
 
1.6%
1 3044
 
13.1%
0 19658
84.6%

has_solution
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing317
Missing (%)1.4%
Memory size1.4 MiB

odoo_success_state
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing351
Missing (%)1.5%
Memory size837.3 KiB

cicore
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7652
Missing (%)32.9%
Memory size3.8 MiB

access_url
URL

UNIQUE 

Distinct23249
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 MiB
https://exactlyit.com/my/ticket/782701
 
1
https://exactlyit.com/my/ticket/771123
 
1
https://exactlyit.com/my/ticket/771167
 
1
https://exactlyit.com/my/ticket/771211
 
1
https://exactlyit.com/my/ticket/771112
 
1
Other values (23244)
23244 
ValueCountFrequency (%)
https://exactlyit.com/my/ticket/782701 1
 
< 0.1%
https://exactlyit.com/my/ticket/771123 1
 
< 0.1%
https://exactlyit.com/my/ticket/771167 1
 
< 0.1%
https://exactlyit.com/my/ticket/771211 1
 
< 0.1%
https://exactlyit.com/my/ticket/771112 1
 
< 0.1%
https://exactlyit.com/my/ticket/771230 1
 
< 0.1%
https://exactlyit.com/my/ticket/771124 1
 
< 0.1%
https://exactlyit.com/my/ticket/771217 1
 
< 0.1%
https://exactlyit.com/my/ticket/771228 1
 
< 0.1%
https://lummus.exactlyit.com/my/ticket/769738 1
 
< 0.1%
Other values (23239) 23239
> 99.9%
ValueCountFrequency (%)
https 23249
100.0%
ValueCountFrequency (%)
exactlyit.com 21356
91.9%
lummus.exactlyit.com 1893
 
8.1%
ValueCountFrequency (%)
/my/ticket/782701 1
 
< 0.1%
/my/ticket/771123 1
 
< 0.1%
/my/ticket/771167 1
 
< 0.1%
/my/ticket/771211 1
 
< 0.1%
/my/ticket/771112 1
 
< 0.1%
/my/ticket/771230 1
 
< 0.1%
/my/ticket/771124 1
 
< 0.1%
/my/ticket/771217 1
 
< 0.1%
/my/ticket/771228 1
 
< 0.1%
/my/ticket/769738 1
 
< 0.1%
Other values (23239) 23239
> 99.9%
ValueCountFrequency (%)
23249
100.0%
ValueCountFrequency (%)
23249
100.0%

is_alert
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Alert
15308 
Others
7941 

Length

Max length6
Median length5
Mean length5.3415631
Min length5

Characters and Unicode

Total characters124186
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAlert
2nd rowAlert
3rd rowAlert
4th rowAlert
5th rowAlert

Common Values

ValueCountFrequency (%)
Alert 15308
65.8%
Others 7941
34.2%

Length

2024-06-22T10:05:59.943645image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-22T10:05:59.994128image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
alert 15308
65.8%
others 7941
34.2%

Most occurring characters

ValueCountFrequency (%)
r 23249
18.7%
e 23249
18.7%
t 23249
18.7%
l 15308
12.3%
A 15308
12.3%
O 7941
 
6.4%
h 7941
 
6.4%
s 7941
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 124186
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 23249
18.7%
e 23249
18.7%
t 23249
18.7%
l 15308
12.3%
A 15308
12.3%
O 7941
 
6.4%
h 7941
 
6.4%
s 7941
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 124186
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 23249
18.7%
e 23249
18.7%
t 23249
18.7%
l 15308
12.3%
A 15308
12.3%
O 7941
 
6.4%
h 7941
 
6.4%
s 7941
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 124186
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 23249
18.7%
e 23249
18.7%
t 23249
18.7%
l 15308
12.3%
A 15308
12.3%
O 7941
 
6.4%
h 7941
 
6.4%
s 7941
 
6.4%

team
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing350
Missing (%)1.5%
Memory size5.3 MiB

sla_resolution_status
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.0 MiB

stage_id_name
Categorical

IMBALANCE 

Distinct11
Distinct (%)< 0.1%
Missing28
Missing (%)0.1%
Memory size1.4 MiB
Solved
14568 
Closed
7145 
Assigned
 
407
In Progress
 
321
With Customer
 
228
Other values (6)
 
552

Length

Max length17
Median length6
Mean length6.2213944
Min length4

Characters and Unicode

Total characters144467
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSolved
2nd rowSolved
3rd rowSolved
4th rowSolved
5th rowSolved

Common Values

ValueCountFrequency (%)
Solved 14568
62.7%
Closed 7145
30.7%
Assigned 407
 
1.8%
In Progress 321
 
1.4%
With Customer 228
 
1.0%
Cancelled 179
 
0.8%
Open 164
 
0.7%
With Vendor 113
 
0.5%
With User 47
 
0.2%
Postponed 41
 
0.2%
(Missing) 28
 
0.1%

Length

2024-06-22T10:06:00.050534image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
solved 14568
60.9%
closed 7145
29.8%
assigned 407
 
1.7%
with 388
 
1.6%
in 321
 
1.3%
progress 321
 
1.3%
customer 228
 
1.0%
cancelled 179
 
0.7%
open 164
 
0.7%
vendor 113
 
0.5%
Other values (4) 104
 
0.4%

Most occurring characters

ValueCountFrequency (%)
e 23408
16.2%
o 22473
15.6%
d 22453
15.5%
l 22071
15.3%
S 14568
10.1%
v 14568
10.1%
s 8925
 
6.2%
C 7552
 
5.2%
n 1233
 
0.9%
r 1038
 
0.7%
Other values (19) 6178
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 144467
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 23408
16.2%
o 22473
15.6%
d 22453
15.5%
l 22071
15.3%
S 14568
10.1%
v 14568
10.1%
s 8925
 
6.2%
C 7552
 
5.2%
n 1233
 
0.9%
r 1038
 
0.7%
Other values (19) 6178
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 144467
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 23408
16.2%
o 22473
15.6%
d 22453
15.5%
l 22071
15.3%
S 14568
10.1%
v 14568
10.1%
s 8925
 
6.2%
C 7552
 
5.2%
n 1233
 
0.9%
r 1038
 
0.7%
Other values (19) 6178
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 144467
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 23408
16.2%
o 22473
15.6%
d 22453
15.5%
l 22071
15.3%
S 14568
10.1%
v 14568
10.1%
s 8925
 
6.2%
C 7552
 
5.2%
n 1233
 
0.9%
r 1038
 
0.7%
Other values (19) 6178
 
4.3%

sla_response_status
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.2 MiB

primary_root_cause_id
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing368
Missing (%)1.6%
Memory size729.8 KiB

user_count
Real number (ℝ)

Distinct16
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4856983
Minimum0
Maximum15
Zeros35
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:06:00.106668image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile5
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2819471
Coefficient of variation (CV)0.51572917
Kurtosis4.571734
Mean2.4856983
Median Absolute Deviation (MAD)1
Skewness1.4130818
Sum57790
Variance1.6433885
MonotonicityNot monotonic
2024-06-22T10:06:00.164143image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 7611
32.7%
3 6654
28.6%
1 5243
22.6%
4 2272
 
9.8%
5 825
 
3.5%
6 345
 
1.5%
7 148
 
0.6%
8 58
 
0.2%
0 35
 
0.2%
9 32
 
0.1%
Other values (6) 26
 
0.1%
ValueCountFrequency (%)
0 35
 
0.2%
1 5243
22.6%
2 7611
32.7%
3 6654
28.6%
4 2272
 
9.8%
5 825
 
3.5%
6 345
 
1.5%
7 148
 
0.6%
8 58
 
0.2%
9 32
 
0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
14 1
 
< 0.1%
13 3
 
< 0.1%
12 3
 
< 0.1%
11 8
 
< 0.1%
10 10
 
< 0.1%
9 32
 
0.1%
8 58
 
0.2%
7 148
0.6%
6 345
1.5%

handle_type
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.7 MiB
Monitoring Ticket
15308 
Service Desk handled
7941 

Length

Max length20
Median length17
Mean length18.024689
Min length17

Characters and Unicode

Total characters419056
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMonitoring Ticket
2nd rowMonitoring Ticket
3rd rowMonitoring Ticket
4th rowMonitoring Ticket
5th rowMonitoring Ticket

Common Values

ValueCountFrequency (%)
Monitoring Ticket 15308
65.8%
Service Desk handled 7941
34.2%

Length

2024-06-22T10:06:00.233601image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-22T10:06:00.284127image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
monitoring 15308
28.1%
ticket 15308
28.1%
service 7941
14.6%
desk 7941
14.6%
handled 7941
14.6%

Most occurring characters

ValueCountFrequency (%)
i 53865
12.9%
e 47072
11.2%
n 38557
 
9.2%
31190
 
7.4%
t 30616
 
7.3%
o 30616
 
7.3%
k 23249
 
5.5%
r 23249
 
5.5%
c 23249
 
5.5%
d 15882
 
3.8%
Other values (10) 101511
24.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 419056
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 53865
12.9%
e 47072
11.2%
n 38557
 
9.2%
31190
 
7.4%
t 30616
 
7.3%
o 30616
 
7.3%
k 23249
 
5.5%
r 23249
 
5.5%
c 23249
 
5.5%
d 15882
 
3.8%
Other values (10) 101511
24.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 419056
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 53865
12.9%
e 47072
11.2%
n 38557
 
9.2%
31190
 
7.4%
t 30616
 
7.3%
o 30616
 
7.3%
k 23249
 
5.5%
r 23249
 
5.5%
c 23249
 
5.5%
d 15882
 
3.8%
Other values (10) 101511
24.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 419056
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 53865
12.9%
e 47072
11.2%
n 38557
 
9.2%
31190
 
7.4%
t 30616
 
7.3%
o 30616
 
7.3%
k 23249
 
5.5%
r 23249
 
5.5%
c 23249
 
5.5%
d 15882
 
3.8%
Other values (10) 101511
24.2%
Distinct68
Distinct (%)0.3%
Missing362
Missing (%)1.6%
Memory size1.3 MiB
2024-06-22T10:06:00.399786image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length39
Median length0
Mean length3.5543322
Min length0

Characters and Unicode

Total characters81348
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
desk 1185
 
10.9%
center 1132
 
10.4%
operations 973
 
8.9%
service 666
 
6.1%
global 665
 
6.1%
it 567
 
5.2%
help 450
 
4.1%
converge 429
 
3.9%
network 427
 
3.9%
internal 422
 
3.9%
Other values (92) 3996
36.6%
2024-06-22T10:06:00.617930image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 10408
 
12.8%
7624
 
9.4%
r 6509
 
8.0%
t 5050
 
6.2%
n 4837
 
5.9%
o 3661
 
4.5%
s 3382
 
4.2%
a 3335
 
4.1%
C 3160
 
3.9%
i 2944
 
3.6%
Other values (43) 30438
37.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 81348
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 10408
 
12.8%
7624
 
9.4%
r 6509
 
8.0%
t 5050
 
6.2%
n 4837
 
5.9%
o 3661
 
4.5%
s 3382
 
4.2%
a 3335
 
4.1%
C 3160
 
3.9%
i 2944
 
3.6%
Other values (43) 30438
37.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 81348
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 10408
 
12.8%
7624
 
9.4%
r 6509
 
8.0%
t 5050
 
6.2%
n 4837
 
5.9%
o 3661
 
4.5%
s 3382
 
4.2%
a 3335
 
4.1%
C 3160
 
3.9%
i 2944
 
3.6%
Other values (43) 30438
37.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 81348
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 10408
 
12.8%
7624
 
9.4%
r 6509
 
8.0%
t 5050
 
6.2%
n 4837
 
5.9%
o 3661
 
4.5%
s 3382
 
4.2%
a 3335
 
4.1%
C 3160
 
3.9%
i 2944
 
3.6%
Other values (43) 30438
37.4%

secondary_root_cause_id
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing368
Missing (%)1.6%
Memory size729.8 KiB

secondary_root_cause_id_name
Categorical

IMBALANCE  MISSING 

Distinct6
Distinct (%)< 0.1%
Missing368
Missing (%)1.6%
Memory size1.3 MiB
22869 
Caused by Vendor
 
6
Unknown
 
2
Power / electrical issue
 
2
System Error
 
1

Length

Max length24
Median length0
Mean length0.0080416066
Min length0

Characters and Unicode

Total characters184
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
22869
98.4%
Caused by Vendor 6
 
< 0.1%
Unknown 2
 
< 0.1%
Power / electrical issue 2
 
< 0.1%
System Error 1
 
< 0.1%
Hardware issue 1
 
< 0.1%
(Missing) 368
 
1.6%

Length

2024-06-22T10:06:00.693793image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-22T10:06:00.748071image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
caused 6
18.8%
by 6
18.8%
vendor 6
18.8%
issue 3
9.4%
unknown 2
 
6.2%
2
 
6.2%
power 2
 
6.2%
electrical 2
 
6.2%
system 1
 
3.1%
error 1
 
3.1%

Most occurring characters

ValueCountFrequency (%)
e 23
12.5%
20
 
10.9%
r 15
 
8.2%
d 13
 
7.1%
s 13
 
7.1%
n 12
 
6.5%
o 11
 
6.0%
a 10
 
5.4%
u 9
 
4.9%
y 7
 
3.8%
Other values (16) 51
27.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 184
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 23
12.5%
20
 
10.9%
r 15
 
8.2%
d 13
 
7.1%
s 13
 
7.1%
n 12
 
6.5%
o 11
 
6.0%
a 10
 
5.4%
u 9
 
4.9%
y 7
 
3.8%
Other values (16) 51
27.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 184
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 23
12.5%
20
 
10.9%
r 15
 
8.2%
d 13
 
7.1%
s 13
 
7.1%
n 12
 
6.5%
o 11
 
6.0%
a 10
 
5.4%
u 9
 
4.9%
y 7
 
3.8%
Other values (16) 51
27.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 184
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 23
12.5%
20
 
10.9%
r 15
 
8.2%
d 13
 
7.1%
s 13
 
7.1%
n 12
 
6.5%
o 11
 
6.0%
a 10
 
5.4%
u 9
 
4.9%
y 7
 
3.8%
Other values (16) 51
27.7%

technique_id_name
Text

MISSING 

Distinct80
Distinct (%)0.3%
Missing362
Missing (%)1.6%
Memory size1.3 MiB
2024-06-22T10:06:00.897406image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length46
Median length0
Mean length1.2379954
Min length0

Characters and Unicode

Total characters28334
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.1%

Sample

1st rowApplication Layer Protocol
2nd row
3rd row
4th rowPhishing
5th row
ValueCountFrequency (%)
accounts 319
 
8.6%
valid 318
 
8.6%
protocol 187
 
5.1%
brute 179
 
4.8%
force 179
 
4.8%
application 151
 
4.1%
phishing 142
 
3.8%
layer 142
 
3.8%
execution 138
 
3.7%
user 131
 
3.5%
Other values (123) 1807
48.9%
2024-06-22T10:06:01.143743image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2338
 
8.3%
i 2199
 
7.8%
e 2151
 
7.6%
2138
 
7.5%
t 2132
 
7.5%
n 2078
 
7.3%
c 1955
 
6.9%
r 1722
 
6.1%
a 1452
 
5.1%
s 1110
 
3.9%
Other values (42) 9059
32.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 28334
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2338
 
8.3%
i 2199
 
7.8%
e 2151
 
7.6%
2138
 
7.5%
t 2132
 
7.5%
n 2078
 
7.3%
c 1955
 
6.9%
r 1722
 
6.1%
a 1452
 
5.1%
s 1110
 
3.9%
Other values (42) 9059
32.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 28334
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2338
 
8.3%
i 2199
 
7.8%
e 2151
 
7.6%
2138
 
7.5%
t 2132
 
7.5%
n 2078
 
7.3%
c 1955
 
6.9%
r 1722
 
6.1%
a 1452
 
5.1%
s 1110
 
3.9%
Other values (42) 9059
32.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 28334
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2338
 
8.3%
i 2199
 
7.8%
e 2151
 
7.6%
2138
 
7.5%
t 2132
 
7.5%
n 2078
 
7.3%
c 1955
 
6.9%
r 1722
 
6.1%
a 1452
 
5.1%
s 1110
 
3.9%
Other values (42) 9059
32.0%

followers_count
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3552841
Minimum0
Maximum21
Zeros10859
Zeros (%)46.7%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:06:01.223110image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum21
Range21
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8493613
Coefficient of variation (CV)1.3645562
Kurtosis4.3462306
Mean1.3552841
Median Absolute Deviation (MAD)1
Skewness1.8351988
Sum31509
Variance3.4201374
MonotonicityNot monotonic
2024-06-22T10:06:01.282407image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 10859
46.7%
1 5066
21.8%
3 2331
 
10.0%
2 2068
 
8.9%
4 1252
 
5.4%
5 817
 
3.5%
6 369
 
1.6%
7 220
 
0.9%
8 100
 
0.4%
9 78
 
0.3%
Other values (6) 89
 
0.4%
ValueCountFrequency (%)
0 10859
46.7%
1 5066
21.8%
2 2068
 
8.9%
3 2331
 
10.0%
4 1252
 
5.4%
5 817
 
3.5%
6 369
 
1.6%
7 220
 
0.9%
8 100
 
0.4%
9 78
 
0.3%
ValueCountFrequency (%)
21 1
 
< 0.1%
14 2
 
< 0.1%
13 5
 
< 0.1%
12 10
 
< 0.1%
11 21
 
0.1%
10 50
 
0.2%
9 78
 
0.3%
8 100
 
0.4%
7 220
0.9%
6 369
1.6%

technique_id
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing362
Missing (%)1.6%
Memory size735.5 KiB

location
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)1.6%
Memory size1.3 MiB

team_level
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Level 2
15865 
Level 1
7384 

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters162743
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLevel 2
2nd rowLevel 2
3rd rowLevel 2
4th rowLevel 2
5th rowLevel 2

Common Values

ValueCountFrequency (%)
Level 2 15865
68.2%
Level 1 7384
31.8%

Length

2024-06-22T10:06:01.348231image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-22T10:06:01.396890image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
level 23249
50.0%
2 15865
34.1%
1 7384
 
15.9%

Most occurring characters

ValueCountFrequency (%)
e 46498
28.6%
L 23249
14.3%
v 23249
14.3%
l 23249
14.3%
23249
14.3%
2 15865
 
9.7%
1 7384
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 162743
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 46498
28.6%
L 23249
14.3%
v 23249
14.3%
l 23249
14.3%
23249
14.3%
2 15865
 
9.7%
1 7384
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 162743
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 46498
28.6%
L 23249
14.3%
v 23249
14.3%
l 23249
14.3%
23249
14.3%
2 15865
 
9.7%
1 7384
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 162743
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 46498
28.6%
L 23249
14.3%
v 23249
14.3%
l 23249
14.3%
23249
14.3%
2 15865
 
9.7%
1 7384
 
4.5%

total_hours_spent
Real number (ℝ)

ZEROS 

Distinct252
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.16865973
Minimum-409.82
Maximum282.3
Zeros18161
Zeros (%)78.1%
Negative2
Negative (%)< 0.1%
Memory size181.8 KiB
2024-06-22T10:06:01.462670image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-409.82
5-th percentile0
Q10
median0
Q30
95-th percentile0.5
Maximum282.3
Range692.12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.1351816
Coefficient of variation (CV)24.517896
Kurtosis6064.9303
Mean0.16865973
Median Absolute Deviation (MAD)0
Skewness-10.935313
Sum3921.17
Variance17.099727
MonotonicityNot monotonic
2024-06-22T10:06:01.540078image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18161
78.1%
0.17 1133
 
4.9%
0.08 995
 
4.3%
0.5 324
 
1.4%
0.33 318
 
1.4%
0.25 178
 
0.8%
0.42 92
 
0.4%
0.67 75
 
0.3%
1 73
 
0.3%
0.02 65
 
0.3%
Other values (242) 1835
 
7.9%
ValueCountFrequency (%)
-409.82 1
 
< 0.1%
-0.67 1
 
< 0.1%
0 18161
78.1%
0.02 65
 
0.3%
0.03 4
 
< 0.1%
0.05 4
 
< 0.1%
0.08 995
 
4.3%
0.1 34
 
0.1%
0.12 37
 
0.2%
0.13 36
 
0.2%
ValueCountFrequency (%)
282.3 1
< 0.1%
272.07 1
< 0.1%
155.93 1
< 0.1%
151.3 1
< 0.1%
76.92 1
< 0.1%
71.45 1
< 0.1%
49.9 1
< 0.1%
37.08 1
< 0.1%
26.47 1
< 0.1%
24.83 1
< 0.1%

first_assigned_team
Real number (ℝ)

MISSING  ZEROS 

Distinct68
Distinct (%)0.3%
Missing362
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean117.27111
Minimum0
Maximum1297
Zeros19599
Zeros (%)84.3%
Negative0
Negative (%)0.0%
Memory size181.8 KiB
2024-06-22T10:06:01.621262image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1142
Maximum1297
Range1297
Interquartile range (IQR)0

Descriptive statistics

Standard deviation342.05217
Coefficient of variation (CV)2.9167641
Kurtosis5.334255
Mean117.27111
Median Absolute Deviation (MAD)0
Skewness2.68043
Sum2683984
Variance116999.69
MonotonicityNot monotonic
2024-06-22T10:06:01.702117image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 19599
84.3%
1142 427
 
1.8%
1246 385
 
1.7%
1216 321
 
1.4%
2 287
 
1.2%
1155 273
 
1.2%
373 259
 
1.1%
11 183
 
0.8%
1 158
 
0.7%
944 115
 
0.5%
Other values (58) 880
 
3.8%
(Missing) 362
 
1.6%
ValueCountFrequency (%)
0 19599
84.3%
1 158
 
0.7%
2 287
 
1.2%
8 55
 
0.2%
9 21
 
0.1%
10 11
 
< 0.1%
11 183
 
0.8%
322 1
 
< 0.1%
328 2
 
< 0.1%
332 1
 
< 0.1%
ValueCountFrequency (%)
1297 2
 
< 0.1%
1267 1
 
< 0.1%
1250 2
 
< 0.1%
1246 385
1.7%
1219 5
 
< 0.1%
1217 65
 
0.3%
1216 321
1.4%
1198 1
 
< 0.1%
1196 3
 
< 0.1%
1194 1
 
< 0.1%

cicore_id_business_process
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23030
Missing (%)99.1%
Memory size742.2 KiB

ml_search
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23024
Missing (%)99.0%
Memory size772.4 KiB

Interactions

2024-06-22T10:05:26.923228image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T09:53:27.331014image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T09:53:45.269692image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T09:54:04.168753image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T09:54:23.142978image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T09:54:41.572101image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T09:54:59.846466image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:00:34.213505image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:00:52.195489image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:01:10.873524image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:01:29.706782image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:01:47.411784image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-06-22T10:03:53.353218image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:04:12.750684image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:04:31.423507image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:04:49.894809image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:05:08.998357image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-06-22T10:05:26.863592image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Missing values

2024-06-22T10:05:47.364862image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-06-22T10:05:47.716677image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-06-22T10:05:48.571116image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

write_datepartner_emailcurrent_durationmessage_total_countclose_datepostponed_reasonteam_idteam_id_namesubtechnique_idassignment_countgeo_pointpartner_id_nameinternal_team_departmentcustomer_cms_recordsolutioncommercial_partner_id_nameproduct_iddragonfly_customertime_dayprimary_root_cause_id_nameidcreate_datesubtechnique_id_nametag_idslast_comming_fromdescription_plainstage_idalert_criteriaassign_minticket_type_sequenceproduct_id_nameactivecustomer_cms_record_namecicore_iddate_tzticket_type_iduser_idtactic_id_namenametime_hourticket_classstage_sequencetactic_idticket_sourcedescriptioncommercial_partner_longitudeuser_id_namelast_edit_customercicore_id_namelast_edit_internalpartner_idticket_type_relatedticket_type_id_namestage_change_countcommercial_partner_idcommercial_partner_latitudeteam_change_counthas_solutionodoo_success_statecicoreaccess_urlis_alertteamsla_resolution_statusstage_id_namesla_response_statusprimary_root_cause_iduser_counthandle_typefirst_assigned_team_namesecondary_root_cause_idsecondary_root_cause_id_nametechnique_id_namefollowers_counttechnique_idlocationteam_leveltotal_hours_spentfirst_assigned_teamcicore_id_business_processml_search
02024-06-10 15:46:450.00000062024-06-10 15:46:46False1216.0CBI - SOC35210.0, 0.0Northside Hospital (CPC CBI) ITSM MonitoringMSO7118<p><br></p>Northside Hospital (CPC CBI) ITSM23069Northside HospitalMonday7711232024-06-10 14:35:38Web Protocols[]Web\n\n    [EXTERNAL SENDER]\nThis message was sent to you automatically by Exabeam on the following high risk event by an asset.\nHigh risk session by asset: mm3he87-bfl with a risk score of 150 \nAsset Name: mm3he87-bfl \nAsset IP: 99.16.42.10\nTop user for this asset: Louchion Wright, Tiffany Williams\nSession Start Time: June 10 2024, 12:00AM (GMT) \nSession End Time: June 11 2024, 12:00AM (GMT) \nTop Risk Reason: A security alert is associated with the asset. \nThis is a SOC Alert for Northside Hospital Exabeam Advanced Analytics SIEM.\n\n\n    [EXTERNAL SENDER]\nThis message was sent to you automatically by Exabeam on the following high risk event by an asset.\nHigh risk session by asset: radjht60-nfshi with a risk score of 95 \nAsset Name: radjht60-nfshi \nAsset IP: 10.47.10.173\nTop user for this asset: Radiology iis\nSession Start Time: June 10 2024, 12:00AM (GMT) \nSession End Time: June 11 2024, 12:00AM (GMT) \nTop Risk Reason: A security alert is associated with the asset. This is the first occurrence of this security alert name on this asset\nThis is a SOC Alert for Northside Hospital Exabeam Advanced Analytics SIEM.\n\n3.0Unclassified54.9913SOC: Escalations: NORHOS-Northside HospitaltrueNorthside Hospital2965017180301380002.027538Command and ControlAlert | Northside Hospital | Northside Hospital Email | NSH VECTRA ALERT (#771123)14Alert6.013Alert<p style="margin-bottom: 0px;"><br>    [EXTERNAL SENDER]<br>This message was sent to you automatically by Exabeam on the following high risk event by an asset.<br>High risk session by asset: mm3he87-bfl with a risk score of 150 <br>Asset Name: mm3he87-bfl <br>Asset IP: 99.16.42.10<br>Top user for this asset: Louchion Wright, Tiffany Williams<br>Session Start Time: June 10 2024, 12:00AM (GMT) <br>Session End Time: June 11 2024, 12:00AM (GMT) <br>Top Risk Reason: A security alert is associated with the asset. <br>This is a SOC Alert for Northside Hospital Exabeam Advanced Analytics SIEM.<br>\n<br>    [EXTERNAL SENDER]<br>This message was sent to you automatically by Exabeam on the following high risk event by an asset.<br>High risk session by asset: radjht60-nfshi with a risk score of 95 <br>Asset Name: radjht60-nfshi <br>Asset IP: 10.47.10.173<br>Top user for this asset: Radiology iis<br>Session Start Time: June 10 2024, 12:00AM (GMT) <br>Session End Time: June 11 2024, 12:00AM (GMT) <br>Top Risk Reason: A security alert is associated with the asset. This is the first occurrence of this security alert name on this asset<br>This is a SOC Alert for Northside Hospital Exabeam Advanced Analytics SIEM.<br></p>0.0000Naiman, Alex2024-06-10 14:35:41SOC Incident Management Northside Hospital2024-06-10 15:46:4751540.0FalseUndefined2515380.0000falseFalse{'cisubtype_id_name': '', 'cistage_id_name': 'Production', 'id': 29650, 'citype_id_name': 'Service', 'cicriticality_id_name': 'Critical'}https://exactlyit.com/my/ticket/771123Alert{'team_category': 'Provider', 'id': 1216, 'team_level': 'Level 2', 'owner_id_name': 'Swisher, Ryan | ExactlyIT Inc'}FalseSolvedFalse03Monitoring Ticket0Application Layer Protocol140AtlantaLevel 20.000.0NaNNaN
12024-06-10 15:42:471@1.com0.53333342024-06-10 15:42:47False1085.0CEC-Intel Services000.0, 0.0Converge TP ITSM MonitoringCEC5588Converge TP0Converge TPMonday7711672024-06-10 15:10:28[]Web\nAlert: Zabbix agent on cec-lex-pkirt.converge.cloud is unreachable for 10 minutes : PROBLEM for cec-lex-pkirt.converge.cloud (Q3H9A5YVD5F47B) \nSeverity: warning\nHostname: cec-lex-pkirt.converge.cloud \nIp: 172.19.32.70 \nName: Zabbix agent on cec-lex-pkirt.converge.cloud is unreachable for 10 minutes \nSeverity: Average \nStatus: PROBLEM \nURL: http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67711068&eventid=78195207 \nIntegration name: Zabbix \n\n3.0Unclassified0.002trueConverge TP1575717180322280005.00Alert: PD - Zabbix | ConvergeTP | Zabbix agent on cec-lex-pkirt.converge.cloud is unreachable for 10 minutes : PROBLEM for cec-lex-pkirt.converge.cloud (#771167)15Alert6.00Alert<p><b>Alert: </b>Zabbix agent on cec-lex-pkirt.converge.cloud is unreachable for 10 minutes : PROBLEM for cec-lex-pkirt.converge.cloud (Q3H9A5YVD5F47B) <br><b>Severity:</b> warning<br><b>Hostname:</b> cec-lex-pkirt.converge.cloud <br><b>Ip:</b> 172.19.32.70 <br><b>Name:</b> Zabbix agent on cec-lex-pkirt.converge.cloud is unreachable for 10 minutes <br><b>Severity:</b> Average <br><b>Status:</b> PROBLEM <br><b>URL:</b> <a href="http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67711068&amp;eventid=78195207" target="_blank">http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67711068&amp;eventid=78195207</a> <br><b>Integration name: Zabbix <br></b></p>0.00002024-06-10 15:42:49CEC-ITSM Processes2000-01-01 00:00:0029834.0IncidentIncident Normal (P3)1274690.0000falseFalse{'cisubtype_id_name': '', 'cistage_id_name': 'Production', 'id': 15757, 'citype_id_name': 'Service', 'cicriticality_id_name': 'Medium'}https://exactlyit.com/my/ticket/771167Alert{'team_category': 'Provider', 'id': 1085, 'team_level': 'Level 2', 'owner_id_name': 'Rose, DJ | ExactlyIT Inc'}FalseSolvedRunning01Monitoring Ticket000Level 20.000.0NaNNaN
22024-06-10 15:45:391@1.com0.06666792024-06-10 15:45:40False1111.0CEC-Storage010.0, 0.0Converge TP ITSM MonitoringCEC5588Converge TP0Converge TPMonday7712112024-06-10 15:41:29[]Web\nAlert: cec-lex-v7000-c01.converge.cloud - Write Cache PC - Stat Peak > 75 : PROBLEM for 172.19.1.40 (Q0O1HK5DO9316R) \nSeverity: warning\nHostname: 172.19.1.40 \nIp: 127.0.0.1 \nName: cec-lex-v7000-c01.converge.cloud - Write Cache PC - Stat Peak > 75 \nSeverity: High \nStatus: PROBLEM \nURL: http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67710729&eventid=78196036 \nIntegration name: CEC-Storage-Zabbix \n\n3.0Unclassified1.892trueConverge TP1575717180340890005.023243Alert: PD - CEC-Storage-Zabbix | ConvergeTP | cec-lex-v7000-c01.converge.cloud - Write Cache PC - Stat Peak > 75 : PROBLEM for 172.19.1.40 (#771211)15Alert6.00Alert<p><b>Alert: </b>cec-lex-v7000-c01.converge.cloud - Write Cache PC - Stat Peak &gt; 75 : PROBLEM for 172.19.1.40 (Q0O1HK5DO9316R) <br><b>Severity:</b> warning<br><b>Hostname:</b> 172.19.1.40 <br><b>Ip:</b> 127.0.0.1 <br><b>Name:</b> cec-lex-v7000-c01.converge.cloud - Write Cache PC - Stat Peak &gt; 75 <br><b>Severity:</b> High <br><b>Status:</b> PROBLEM <br><b>URL:</b> <a href="http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67710729&amp;eventid=78196036" target="_blank">http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67710729&amp;eventid=78196036</a> <br><b>Integration name: CEC-Storage-Zabbix <br></b></p>0.0000Soriano, Azael_EIT2024-06-10 15:45:41CEC-ITSM Processes2000-01-01 00:00:0029834.0IncidentIncident Normal (P3)2274690.0000falseFalse{'cisubtype_id_name': '', 'cistage_id_name': 'Production', 'id': 15757, 'citype_id_name': 'Service', 'cicriticality_id_name': 'Medium'}https://exactlyit.com/my/ticket/771211Alert{'team_category': 'Provider', 'id': 1111, 'team_level': 'Level 2', 'owner_id_name': 'Rose, DJ | ExactlyIT Inc'}FalseSolvedFalse02Monitoring Ticket000Level 20.000.0NaNNaN
32024-06-10 15:56:09False1.46666762024-06-10 15:56:09False2.0EIT-Security Operations Center010.0, 0.0Gilson ITSM MonitoringMSO6903<p><br></p>Gilson ITSM Monitoring0GilsonMonday7711122024-06-10 14:28:58[]Web\n    [EXTERNAL SENDER]\n\n\nReview this incident.                                                                                                                                                                                                                                                                                       \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMicrosoft 365 Defender has detected a security threat in your environment\n\nView incident details:\n\n\n\n\nID\n\n8621\n\n\n\nIncident name\n\nEmail messages removed after delivery​\n\n\n\nSeverity\n\nInformational\n\n\n\nCategories\n\nInitialAccess\n\n\n\nTime\n\nJune 10, 2024 14:25 UTC\n\n\n\nIncident page\n\nhttps://security.microsoft.com/incidents/byalert?alertId=fabb54cb1b-8146-7c15-9000-08dc8957da74&source=incidentemail&tid=ca84dc0c-3fcb-4386-85ad-fbb73fbfded4\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nAccount information\n\nOrganization name Gilson Inc.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n \n\n \n\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrivacy Statement \n\nMicrosoft Corporation, One Microsoft Way, ​Redmond, WA 98052​\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n3.0Unclassified66.242trueGilson017180297380005.030844Initial AccessAlert: Email | gilson | Microsoft 365 Defender has detected a security threat (#771112)14Alert6.014Alert<p style="border:1px; border-style:solid; border-color:#FFCACA; background-color:#ffff00; padding:1px"><span style="font-size:12.0pt; color:black"><strong><span style="background-color:#ff0000">   </span> [EXTERNAL SENDER]</strong></span></p><div><div class="preheader" style="display:none; visibility:hidden; opacity:0; color:#f4f4f4; height:0; width:0; line-height:1px; font-size:1px; max-height:0; max-width:0; overflow:hidden">Review this incident.                                                                                                                                                                                                                                                                                       </div><table class="body" data-made-with-foundation="data-made-with-foundation" role="presentation" style='border-spacing:0; border-collapse:collapse; vertical-align:top; background:#ffffff; height:100%; width:100%; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px'><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><td align="center" class="float-center" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; font-size:14px; line-height:20px; margin:0 auto; float:none; text-align:center' valign="top"><center class="main-container" style="width:100%; min-width:640px"><table align="center" bgcolor="#ffffff" class="float-center" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; margin:0 auto; float:none; text-align:center"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><td style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px'><table align="center" class="container header-container section" dir="ltr" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; background:#ffffff; width:640px; margin:0 auto; text-align:inherit"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><td style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px'><table align="center" class="wrapper outer-wrapper" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; width:100%"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><td class="wrapper-inner" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-right:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px; padding-top:0; padding-bottom:0'><center style="width:100%; min-width:640px"><table align="center" class="row header-section float-center" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; padding:0; width:100%; margin:0 auto; float:none; text-align:center; display:table"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th class="small-12 large-12 columns first last" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; text-align:left; font-size:14px; line-height:20px; margin:0 auto; width:616px; padding-left:24px; padding-right:24px; padding-top:24px; padding-bottom:24px'><table role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; width:100%"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px'> </th><th class="expander" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px; visibility:hidden; width:0; padding:0'></th></tr></tbody></table></th></tr></tbody></table></center></td></tr></tbody></table></td></tr></tbody></table><table align="center" class="container template-container section" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; background:#ffffff; width:640px; margin:0 auto; text-align:inherit"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><td style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px'><table align="center" class="wrapper outer-wrapper" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; width:100%"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><td class="wrapper-inner" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-right:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px; padding-bottom:12px; padding-top:6px'><center style="width:100%; min-width:640px"><table align="center" class="row float-center" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; padding:0; width:100%; margin:0 auto; float:none; text-align:center; display:table"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th class="small-12 large-12 columns first last" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; text-align:left; font-size:14px; line-height:20px; margin:0 auto; width:616px; padding-bottom:12px; padding-left:24px; padding-right:24px; padding-top:6px'><table role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; width:100%"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px'><h1 style='padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; color:inherit; margin-bottom:16px; letter-spacing:-.01em; font-family:Segoe UI Semibold,SegoeUISemibold,Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:600; font-size:28px; line-height:36px; word-wrap:normal'>Microsoft 365 Defender has detected a security threat in your environment</h1><h3 style='padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; color:inherit; margin-bottom:16px; font-family:Segoe UI Semibold,SegoeUISemibold,Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:600; font-size:20px; line-height:28px; word-wrap:normal'>View incident details:</h3><table class="table-default table-heading-rows" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; max-width:592px; width:100%"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th style='border-collapse:collapse; color:#11100f; margin:0; text-align:left; line-height:20px; word-break:break-word; padding-left:6px; padding-top:6px; padding-bottom:6px; font-size:14px; padding-right:12px; vertical-align:top; width:1%; white-space:nowrap; word-wrap:initial; font-family:Segoe UI Semibold,SegoeUISemibold,Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:600; border-top:none'>ID</th><td style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; margin:0; text-align:left; font-size:14px; line-height:20px; word-break:break-word; padding-top:6px; padding-right:6px; padding-bottom:6px; padding-left:12px; border-top:none'>8621</td></tr><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th style='border-collapse:collapse; color:#11100f; margin:0; text-align:left; line-height:20px; word-break:break-word; padding-left:6px; padding-top:6px; padding-bottom:6px; border-top:solid 1px #dedede; font-size:14px; padding-right:12px; vertical-align:top; width:1%; white-space:nowrap; word-wrap:initial; font-family:Segoe UI Semibold,SegoeUISemibold,Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:600'>Incident name</th><td style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; margin:0; text-align:left; font-size:14px; line-height:20px; word-break:break-word; padding-top:6px; padding-right:6px; padding-bottom:6px; border-top:solid 1px #dedede; padding-left:12px'>Email messages removed after delivery​</td></tr><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th style='border-collapse:collapse; color:#11100f; margin:0; text-align:left; line-height:20px; word-break:break-word; padding-left:6px; padding-top:6px; padding-bottom:6px; border-top:solid 1px #dedede; font-size:14px; padding-right:12px; vertical-align:top; width:1%; white-space:nowrap; word-wrap:initial; font-family:Segoe UI Semibold,SegoeUISemibold,Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:600'>Severity</th><td style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; margin:0; text-align:left; font-size:14px; line-height:20px; word-break:break-word; padding-top:6px; padding-right:6px; padding-bottom:6px; border-top:solid 1px #dedede; padding-left:12px'>Informational</td></tr><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th style='border-collapse:collapse; color:#11100f; margin:0; text-align:left; line-height:20px; word-break:break-word; padding-left:6px; padding-top:6px; padding-bottom:6px; border-top:solid 1px #dedede; font-size:14px; padding-right:12px; vertical-align:top; width:1%; white-space:nowrap; word-wrap:initial; font-family:Segoe UI Semibold,SegoeUISemibold,Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:600'>Categories</th><td style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; margin:0; text-align:left; font-size:14px; line-height:20px; word-break:break-word; padding-top:6px; padding-right:6px; padding-bottom:6px; border-top:solid 1px #dedede; padding-left:12px'>InitialAccess</td></tr><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th style='border-collapse:collapse; color:#11100f; margin:0; text-align:left; line-height:20px; word-break:break-word; padding-left:6px; padding-top:6px; padding-bottom:6px; border-top:solid 1px #dedede; font-size:14px; padding-right:12px; vertical-align:top; width:1%; white-space:nowrap; word-wrap:initial; font-family:Segoe UI Semibold,SegoeUISemibold,Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:600'>Time</th><td style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; margin:0; text-align:left; font-size:14px; line-height:20px; word-break:break-word; padding-top:6px; padding-right:6px; padding-bottom:6px; border-top:solid 1px #dedede; padding-left:12px'>June 10, 2024 14:25 UTC</td></tr><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th style='border-collapse:collapse; color:#11100f; margin:0; text-align:left; line-height:20px; word-break:break-word; padding-left:6px; padding-top:6px; padding-bottom:6px; border-top:solid 1px #dedede; font-size:14px; padding-right:12px; vertical-align:top; width:1%; white-space:nowrap; word-wrap:initial; font-family:Segoe UI Semibold,SegoeUISemibold,Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:600; border-bottom:none'>Incident page</th><td class="wrap-word" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; margin:0; text-align:left; font-size:14px; line-height:20px; max-width:592px; display:table-cell; word-break:break-word; padding-top:6px; padding-right:6px; padding-bottom:6px; border-top:solid 1px #dedede; padding-left:12px; border-bottom:none'><a href="https://can01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fnam.safelink.emails.azure.net%2Fredirect%2F%3Fdestination%3Dhttps%253A%252F%252Fsecurity.microsoft.com%252Fincidents%252Fbyalert%253FalertId%253Dfabb54cb1b-8146-7c15-9000-08dc8957da74%2526source%253Dincidentemail%2526tid%253Dca84dc0c-3fcb-4386-85ad-fbb73fbfded4%26p%3DbT0zZjViMDA0My00ZmYzLTRmZTMtYWZjYy04NTM3ODY2NjA1NTMmdT1hZW8mbD1ieWFsZXJ0&amp;data=05|02|eit-odoo.alertdispatcher%40convergetp.com|f4d5f0838a81400dedb108dc89593c9a|e7e3e0637a104f0f9cbc2e661383895e|0|0|638536263570527428|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|0|||&amp;sdata=EK3zGMaoK3XymR0OliG0UU1GB8soV2%2BRyd7%2Fk4DRaMk%3D&amp;reserved=0" originalsrc="https://nam.safelink.emails.azure.net/redirect/?destination=https%3A%2F%2Fsecurity.microsoft.com%2Fincidents%2Fbyalert%3FalertId%3Dfabb54cb1b-8146-7c15-9000-08dc8957da74%26source%3Dincidentemail%26tid%3Dca84dc0c-3fcb-4386-85ad-fbb73fbfded4&amp;p=bT0zZjViMDA0My00ZmYzLTRmZTMtYWZjYy04NTM3ODY2NjA1NTMmdT1hZW8mbD1ieWFsZXJ0" shash="cdBbs12pVdS35ahsQY1ANkrfbvH+6cdPIx7+/hO7/cDvHaQXmQztVr472z3GpORgvA7QkE2YxuE3MgvRlwoQ0ybLvIuczLRfbHf7nmhs4HbtZ591ToJq5KhNNKDXKbOAD262BaJTGttle6mhmh8V4YC/hFSFr+hsgIQZYBMqKco=" style='color:#0078d4; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding:0; text-align:left; line-height:20px; text-decoration:none'>https://security.microsoft.com/incidents/byalert?alertId=fabb54cb1b-8146-7c15-9000-08dc8957da74&amp;source=incidentemail&amp;tid=ca84dc0c-3fcb-4386-85ad-fbb73fbfded4</a></td></tr></tbody></table></th><th class="expander" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px; visibility:hidden; width:0; padding:0'></th></tr></tbody></table></th></tr></tbody></table></center></td></tr></tbody></table><table align="center" class="wrapper outer-wrapper divider-light-top" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; width:100%; border-top:1px solid #eaebec"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><td class="wrapper-inner" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-right:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px; padding-top:12px; padding-bottom:12px'><center style="width:100%; min-width:640px"><table align="center" class="row float-center" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; padding:0; width:100%; margin:0 auto; float:none; text-align:center; display:table"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th class="small-12 large-12 columns first last" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; text-align:left; font-size:14px; line-height:20px; margin:0 auto; width:616px; padding-top:12px; padding-bottom:12px; padding-left:24px; padding-right:24px'><table role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; width:100%"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px'><h2 style='padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; color:inherit; margin-bottom:16px; font-family:Segoe UI Semibold,SegoeUISemibold,Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:600; font-size:24px; line-height:32px; word-wrap:normal'>Account information</h2><p style='color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:16px; line-height:22px; word-wrap:normal; margin-bottom:0'><strong style='font-family:Segoe UI Semibold,SegoeUISemibold,Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:600'>Organization name</strong> Gilson Inc.</p></th><th class="expander" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px; visibility:hidden; width:0; padding:0'></th></tr></tbody></table></th></tr></tbody></table></center></td></tr></tbody></table></td></tr></tbody></table><table align="center" class="container footer-template" dir="ltr" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; background:#ffffff; width:640px; margin:0 auto; text-align:inherit"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><td style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px'><table align="center" class="wrapper outer-wrapper footer-wrapper" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; width:100%; background-color:#F0F0F0"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><td class="wrapper-inner" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-right:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px; padding-top:12px; padding-bottom:12px'><center style="width:100%; min-width:640px"><table class="row image-row" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; padding:0; width:100%; display:table"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th class="small-12 large-12 columns first last" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; text-align:left; font-size:14px; line-height:20px; margin:0 auto; padding-left:24px; padding-right:24px; padding-top:12px; width:auto; padding-bottom:0px'><table role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; width:100%"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px'><table class="social-links" role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; width:auto" valign="middle"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><td style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:1; padding-right:8px'> </td><td style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:1; padding-right:8px'> </td><td style='word-wrap:break-word; 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border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; padding:0; width:100%; display:table"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th class="small-12 large-12 columns first last" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; text-align:left; font-size:14px; line-height:20px; margin:0 auto; padding-left:24px; padding-right:24px; padding-top:12px; padding-bottom:12px; width:auto'><table role="presentation" style="border-spacing:0; border-collapse:collapse; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left; width:100%"><tbody><tr style="padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; vertical-align:top; text-align:left"><th style='word-wrap:break-word; 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font-weight:400; padding:0; text-align:left; line-height:20px; color:#484644; display:inline-block; text-decoration:underline' title="Privacy Statement">Privacy Statement</a> </p><p class="margin-top-8" style='font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; margin-bottom:12px; word-wrap:normal; margin-top:8px; font-size:12px; line-height:16px; color:#484644'>Microsoft Corporation, <span class="no-wrap" style="display:inline-block; word-break:keep-all">One Microsoft Way, ​Redmond, WA 98052​</span></p> </th><th class="expander" style='word-wrap:break-word; border-collapse:collapse; vertical-align:top; color:#11100f; font-family:Segoe UI,SegoeUI,Roboto,"Helvetica Neue",Arial,sans-serif; font-weight:400; padding-top:0; padding-right:0; padding-bottom:0; padding-left:0; margin:0; text-align:left; font-size:14px; line-height:20px; visibility:hidden; width:0; padding:0'></th></tr></tbody></table></th></tr></tbody></table></center></td></tr></tbody></table></td></tr></tbody></table></td></tr></tbody></table></center></td></tr></tbody></table> </div>0.0000Oliver, Daniel2024-06-10 14:29:002024-06-10 15:56:1044558.0IncidentIncident Normal (P3)2445580.0000falseFalseNaNhttps://exactlyit.com/my/ticket/771112Alert{'team_category': 'Provider', 'id': 2, 'team_level': 'Level 2', 'owner_id_name': 'Lovelace, Jimmy_EIT | ExactlyIT Inc'}MetSolvedMet02Monitoring Ticket0Phishing1128Level 20.280.0NaNNaN
42024-06-10 15:56:231@1.com0.03333372024-06-10 15:56:24False1097.0CEC-Network010.0, 0.0Converge TP ITSM MonitoringCEC5588Converge TP0Converge TPMonday7712302024-06-10 15:54:17[]Web\nAlert: LEX/ORD Management IPSec Tunnel may be DOWN : PROBLEM for MSC-ORD-MGT-FW (Q1U341JUYZRGLL) \nSeverity: warning\nHostname: MSC-ORD-MGT-FW \nIp: 172.18.0.19 \nName: LEX/ORD Management IPSec Tunnel may be DOWN \nSeverity: High \nStatus: PROBLEM \nURL: http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67811389&eventid=78196413 \nIntegration name: Zabbix \n\n3.0Unclassified0.911trueConverge TP3057917180348570004.01601Alert: PD - Zabbix | ConvergeTP | LEX/ORD Management IPSec Tunnel may be DOWN : PROBLEM for MSC-ORD-MGT-FW (#771230)15Alert6.00Alert<p><b>Alert: </b>LEX/ORD Management IPSec Tunnel may be DOWN : PROBLEM for MSC-ORD-MGT-FW (Q1U341JUYZRGLL) <br><b>Severity:</b> warning<br><b>Hostname:</b> MSC-ORD-MGT-FW <br><b>Ip:</b> 172.18.0.19 <br><b>Name:</b> LEX/ORD Management IPSec Tunnel may be DOWN <br><b>Severity:</b> High <br><b>Status:</b> PROBLEM <br><b>URL:</b> <a href="http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67811389&amp;eventid=78196413" target="_blank">http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67811389&amp;eventid=78196413</a> <br><b>Integration name: Zabbix <br></b></p>0.0000Bravo, Fernando_EIT2024-06-10 15:56:25msc-ord-mgt-fw012000-01-01 00:00:0029834.0IncidentIncident High (P2)2274690.0000falseFalse{'cisubtype_id_name': 'Firewall', 'cistage_id_name': 'Production', 'id': 30579, 'citype_id_name': 'Network', 'cicriticality_id_name': 'High'}https://exactlyit.com/my/ticket/771230Alert{'team_category': 'Provider', 'id': 1097, 'team_level': 'Level 2', 'owner_id_name': 'Dillon, Matthew | ExactlyIT Inc'}FalseSolvedMet02Monitoring Ticket000Level 20.000.0NaNNaN
52024-06-10 15:57:280.00000062024-06-10 15:57:29False1216.0CBI - SOC010.0, 0.0Hemlock Semiconductor Operations LLC (CPC CBI) ITSM MonitoringMSO7111<p><br></p>Hemlock Semiconductor Operations LLC (CPC CBI) ITSM23062Hemlock Semiconductor Operations LLCMonday7711242024-06-10 14:37:56[]Web\n\n \nFrom: SVC-Sentinel-Email \nSent: Monday, June 10, 2024 10:37:38 AM (UTC-05:00) Eastern Time (US & Canada)\nTo: Freshservice Automator \nSubject: New Azure Sentinel Incident - Explicit MFA Deny involving one user\n    [EXTERNAL SENDER]\nNew incident created in Azure Sentinel. Incident details:\nIncident title:\nExplicit MFA Deny involving one user\nIncident ID:\n57730\nCreation time:\n2024-06-10T14:30:15.64Z\nSeverity:\nMedium\nAlert providers:\nAzure Sentinel\nTactics:\nDescription:\nEntities:\nEntity\nEntity Type\nMALEKADELI, ALI\nAccount\n174.81.204.69\nIp\nMobile Apps and Desktop clients\nUrl\nIncident link:\nhttps://portal.azure.com/#asset/Microsoft_Azure_Security_Insights/Incident/subscriptions/e17b8987-5b54-46bf-bf61-d8510b050cfc/resourceGroups/hsc-loganalytics-sentinel/providers/Microsoft.OperationalInsights/workspaces/hsc-loganalytics-sentinel/providers/Microsoft.SecurityInsights/Incidents/9ca15822-ec06-4124-82b2-c6144269fea5\nDisclaimer: This e-mail transmission and any files that accompany it may contain confidential or proprietary information of Hemlock Semiconductor. The information is intended only for the use of the individual\n or entity named. If you are not the intended recipient, you are hereby notified that any disclosure, copying, distribution, or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this e-mail\n transmission in error, please immediately notify the sender and delete the message from your system.\n\n3.0Unclassified67.1413SOC: Escalations: HEMLOCK-HemlocktrueHemlock Semiconductor Operations LLC2964317180302760002.026595Initial AccessAlert | Hemlock Semiconductor Operations LLC | Hemlock Semiconductor Operations LLC Email | FW: New Azure Sentinel Incident - Explicit MFA Deny involving one user (#771124)14Alert6.014Alert<p style="margin-bottom: 0px;"><br> <br>From: SVC-Sentinel-Email <br>Sent: Monday, June 10, 2024 10:37:38 AM (UTC-05:00) Eastern Time (US &amp; Canada)<br>To: Freshservice Automator <br>Subject: New Azure Sentinel Incident - Explicit MFA Deny involving one user<br>    [EXTERNAL SENDER]<br>New incident created in Azure Sentinel. Incident details:<br>Incident title:<br>Explicit MFA Deny involving one user<br>Incident ID:<br>57730<br>Creation time:<br>2024-06-10T14:30:15.64Z<br>Severity:<br>Medium<br>Alert providers:<br>Azure Sentinel<br>Tactics:<br>Description:<br>Entities:<br>Entity<br>Entity Type<br>MALEKADELI, ALI<br>Account<br>174.81.204.69<br>Ip<br>Mobile Apps and Desktop clients<br>Url<br>Incident link:<br>https://portal.azure.com/#asset/Microsoft_Azure_Security_Insights/Incident/subscriptions/e17b8987-5b54-46bf-bf61-d8510b050cfc/resourceGroups/hsc-loganalytics-sentinel/providers/Microsoft.OperationalInsights/workspaces/hsc-loganalytics-sentinel/providers/Microsoft.SecurityInsights/Incidents/9ca15822-ec06-4124-82b2-c6144269fea5<br>Disclaimer: This e-mail transmission and any files that accompany it may contain confidential or proprietary information of Hemlock Semiconductor. The information is intended only for the use of the individual<br> or entity named. If you are not the intended recipient, you are hereby notified that any disclosure, copying, distribution, or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this e-mail<br> transmission in error, please immediately notify the sender and delete the message from your system.<br></p>0.0000Davis, Alex2024-06-10 14:37:59SOC Incident Management Hemlock2024-06-10 15:57:3051498.0FalseUndefined2514960.0000falseFalse{'cisubtype_id_name': '', 'cistage_id_name': 'Production', 'id': 29643, 'citype_id_name': 'Service', 'cicriticality_id_name': 'Critical'}https://exactlyit.com/my/ticket/771124Alert{'team_category': 'Provider', 'id': 1216, 'team_level': 'Level 2', 'owner_id_name': 'Swisher, Ryan | ExactlyIT Inc'}FalseSolvedFalse03Monitoring Ticket0Valid Accounts1136HemlockLevel 20.200.0NaNNaN
62024-06-10 15:54:351@1.com0.11666742024-06-10 15:53:39False1085.0CEC-Intel Services000.0, 0.0Converge TP ITSM MonitoringCEC5588Converge TP0Converge TPMonday7712172024-06-10 15:46:25[]Web\nAlert: Zabbix agent on VMMS-RiseBaking-USTUCBSA006 is unreachable for 20 minutes : PROBLEM for 10.117.170.132 (Q2TSB1PEIKXBMF) \nSeverity: warning\nHostname: 10.117.170.132 \nIp: 10.117.170.132 \nName: Zabbix agent on VMMS-RiseBaking-USTUCBSA006 is unreachable for 20 minutes \nSeverity: High \nStatus: PROBLEM \nURL: http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67784680&eventid=78196162 \nIntegration name: Zabbix \n\n3.0Unclassified0.001trueConverge TP1575717180343850004.00Alert: PD - Zabbix | ConvergeTP | Zabbix agent on VMMS-RiseBaking-USTUCBSA006 is unreachable for 20 minutes : PROBLEM for 10.117.170.132 (#771217)15Alert6.00Alert<p><b>Alert: </b>Zabbix agent on VMMS-RiseBaking-USTUCBSA006 is unreachable for 20 minutes : PROBLEM for 10.117.170.132 (Q2TSB1PEIKXBMF) <br><b>Severity:</b> warning<br><b>Hostname:</b> 10.117.170.132 <br><b>Ip:</b> 10.117.170.132 <br><b>Name:</b> Zabbix agent on VMMS-RiseBaking-USTUCBSA006 is unreachable for 20 minutes <br><b>Severity:</b> High <br><b>Status:</b> PROBLEM <br><b>URL:</b> <a href="http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67784680&amp;eventid=78196162" target="_blank">http://zabbix.converge.cloud//zabbix/tr_events.php?triggerid=67784680&amp;eventid=78196162</a> <br><b>Integration name: Zabbix <br></b></p>0.00002024-06-10 15:53:41CEC-ITSM Processes2000-01-01 00:00:0029834.0IncidentIncident High (P2)1274690.0000falseFalse{'cisubtype_id_name': '', 'cistage_id_name': 'Production', 'id': 15757, 'citype_id_name': 'Service', 'cicriticality_id_name': 'Medium'}https://exactlyit.com/my/ticket/771217Alert{'team_category': 'Provider', 'id': 1085, 'team_level': 'Level 2', 'owner_id_name': 'Rose, DJ | ExactlyIT Inc'}FalseSolvedRunning01Monitoring Ticket000Level 20.000.0NaNNaN
72024-06-10 15:53:40False0.01666742024-06-10 15:53:40False373.0EIT-Infrastructure Operations Center010.0, 0.0EFG Companies ITSM MonitoringMSO6175EFG Companies ITSM12552EFG CompaniesMonday7712282024-06-10 15:52:11[]WebOriginal title: Failed Connectivity\nDescription: Alert: N-able - EFG Companies > EFG General SV-EFGDC07 Failed Connectivity \nSeverity: Failed\nCustomer: EFG Companies > EFG General\nDevice Name: SV-EFGDC07\nAlertLookup:Connectivity-Failed\nDevice IP: 192.168.3.27\nStatus:\nURL: \nIntegration Name:\n\nAlert Code: IOC000 | Connectivity\n\nNotes:\nNo device note for device SV-EFGDC07 \n\nTo remotely access this device, click the following link:\n\nhttps://ncod504.n-able.com:443/deepLinkAction.do?method=deviceRC&customerID=1787&deviceID=1302526459&language=en_US\n\nDevice Property:\nDevice Description: Network device discovered using Asset Discovery - 1302526459\n\nDevice Property: Enviroment \nDevice Description: Enviroment Network device discovered using Asset Discovery - 1302526459\n\n\nIssue: At 2024-06-10 11:51:43 the Connectivity - service transitioned from a Normal state to a Failed state.\n\nHere are the details of the Connectivity - service:\n\nPacket Loss: 75.00 %\nTime To Live: 124.00 Hops\nAverage Round Trip Time: 39.00 msec\nDNS Resolution: True\n\n----------------------\n\n3.0Unclassified1.480IOC004 | Alert – Connectivity FailedtrueEFG Companies2077417180347310003.01Alert: N-Able | EFG Companies | SV-EFGDC07 | Failed Connectivity (#771228)15Alert6.00Alert<span><b>Original title:</b> Failed Connectivity<br>Description: Alert: N-able - EFG Companies &gt; EFG General SV-EFGDC07 Failed Connectivity <br>Severity: Failed<br>Customer: EFG Companies &gt; EFG General<br>Device Name: SV-EFGDC07<br>AlertLookup:Connectivity-Failed<br>Device IP: 192.168.3.27<br>Status:<br>URL: <br>Integration Name:<br><br>Alert Code: IOC000 | Connectivity<br><br>Notes:<br>No device note for device SV-EFGDC07 <br><br>To remotely access this device, click the following link:<br><br>https://ncod504.n-able.com:443/deepLinkAction.do?method=deviceRC&amp;customerID=1787&amp;deviceID=1302526459&amp;language=en_US<br><br>Device Property:<br>Device Description: Network device discovered using Asset Discovery - 1302526459<br><br>Device Property: Enviroment <br>Device Description: Enviroment Network device discovered using Asset Discovery - 1302526459<br><br><br>Issue: At 2024-06-10 11:51:43 the Connectivity - service transitioned from a Normal state to a Failed state.<br><br>Here are the details of the Connectivity - service:<br><br>Packet Loss: 75.00 %<br>Time To Live: 124.00 Hops<br>Average Round Trip Time: 39.00 msec<br>DNS Resolution: True<br><br>----------------------<br><br></span>0.0000ExactlyIT System Bot2024-06-10 15:53:41SV-EFGDC072000-01-01 00:00:0037361.0IncidentIncident Critical (P1)1373560.0000falseFalse{'cisubtype_id_name': 'Windows', 'cistage_id_name': 'Production', 'id': 20774, 'citype_id_name': 'Operating System', 'cicriticality_id_name': 'High'}https://exactlyit.com/my/ticket/771228Alert{'team_category': 'Provider', 'id': 373, 'team_level': 'Level 2', 'owner_id_name': 'Gaona, Esaul_EIT | ExactlyIT Inc'}MetSolvedMet01Monitoring Ticket000IrvingLevel 20.000.0NaNNaN
82024-06-10 12:32:13ravi.ranjan@lummustech.com0.53333392024-06-10 12:32:15False1250.0Lummus-Document Management FusionLive0140.841, -74.18119999999999Ranjan, RaviMSO1<p><br></p>Lummus Technology, LLC.7442Lummus Technology IncSaturday7697382024-06-08 10:47:57[]Web\n\n\n\n \n\n \n\nFrom: Hazra, Baisakhi \n\nSent: Saturday, June 8, 2024 3:43 PM\n\nTo: FusionAdministration \n\nCc: Ranjan, Ravi ; Kanduri, Satyadevan ; Kummari, Prashanth Kumar \n\nSubject: Fusion Live Service Unavailable\n\n \n\nHello Team,\n\n \n\nCurrently I am facing issues signing in fusion live. Seeking your support. It is showing the below message.\n\n \n\n \n\nBest Regards\n\nBaisakhi\n\nThis transmission is CONFIDENTIAL and the information is intended only for the use of the individual or entity to whom it is addressed. If you are not the intended recipient, or the employee or agent responsible for delivering it to the intended recipient,\n\n you are hereby notified that any use, dissemination, distribution or copying of this communication is STRICTLY PROHIBITED. If you have received the transmission in error, please immediately notify us by e-mail and/or telephone, and delete the transmission\n\n and any attachments from your mailbox. Thank you\n\n\n\n29.0Unclassified0.003Generic Performance IssuetrueLummus Technology Inc3303417178436770006.0435FW: Fusion Live Service Unavailable (#769738)10Incident7.00Email<p style="margin-bottom: 0px;"><br></p><p style="margin-bottom: 0px;"> </p><p style="margin-bottom: 0px;"> </p><p style="margin-bottom: 0px;">From: Hazra, Baisakhi </p><p style="margin-bottom: 0px;">Sent: Saturday, June 8, 2024 3:43 PM</p><p style="margin-bottom: 0px;">To: FusionAdministration </p><p style="margin-bottom: 0px;">Cc: Ranjan, Ravi ; Kanduri, Satyadevan ; Kummari, Prashanth Kumar </p><p style="margin-bottom: 0px;">Subject: Fusion Live Service Unavailable</p><p style="margin-bottom: 0px;"> </p><p style="margin-bottom: 0px;">Hello Team,</p><p style="margin-bottom: 0px;"> </p><p style="margin-bottom: 0px;">Currently I am facing issues signing in fusion live. Seeking your support. It is showing the below message.</p><p style="margin-bottom: 0px;"> </p><p style="margin-bottom: 0px;"> </p><p style="margin-bottom: 0px;">Best Regards</p><p style="margin-bottom: 0px;">Baisakhi</p><p style="margin-bottom: 0px;">This transmission is CONFIDENTIAL and the information is intended only for the use of the individual or entity to whom it is addressed. If you are not the intended recipient, or the employee or agent responsible for delivering it to the intended recipient,</p><p style="margin-bottom: 0px;"> you are hereby notified that any use, dissemination, distribution or copying of this communication is STRICTLY PROHIBITED. If you have received the transmission in error, please immediately notify us by e-mail and/or telephone, and delete the transmission</p><p style="margin-bottom: 0px;"> and any attachments from your mailbox. Thank you</p><p><br></p>-74.1812Edwards, Noreen2024-06-08 10:48:13LUM-FusionLive support requests2024-06-10 12:32:1750520.0IncidentIncident Low (P4)242640.8411falseFalseNaNhttps://lummus.exactlyit.com/my/ticket/769738Others{'team_category': 'Provider', 'id': 1250, 'team_level': 'Level 2', 'owner_id_name': 'Murphy, Kevin J. | Lummus Technology IT Delivery Address'}FalseClosedFalse03Service Desk handled050Abu DhabiLevel 20.000.0NaNNaN
92024-06-10 12:35:38False0.08333332024-06-10 12:35:38False373.0EIT-Infrastructure Operations Center0140.841, -74.18119999999999Lummus ITSM MonitoringMSO1Lummus Technology, LLC.12552Lummus Technology IncMonday7709702024-06-10 12:30:11[]WebOriginal title: Failed Connectivity\nDescription: Alert: N-able - Lummus Technology > LUM Azure Production lum-stbin-pw-01 Failed Connectivity \nSeverity: Failed\nCustomer: Lummus Technology > LUM Azure Production\nDevice Name: lum-stbin-pw-01\nAlertLookup:Connectivity-Failed\nDevice IP: 10.0.16.70\nStatus:\nURL: \nIntegration Name:\n\nAlert Code: IOC000 | Connectivity\n\nNotes:\nNo device note for device lum-stbin-pw-01 \n\nTo remotely access this device, click the following link:\n\nhttps://ncod504.n-able.com:443/deepLinkAction.do?method=deviceRC&customerID=224&deviceID=505477052&language=en_US\n\nDevice Property:\nDevice Description: Network device discovered using Asset Discovery - 505477052\n\nDevice Property: Enviroment \nDevice Description: Enviroment Network device discovered using Asset Discovery - 505477052\n\n\nIssue: At 2024-06-10 08:29:55 the Connectivity - service transitioned from a Normal state to a Failed state.\n\nHere are the details of the Connectivity - service:\n\nPacket Loss: 30.00 %\nTime To Live: 122.00 Hops\nAverage Round Trip Time: 242.00 msec\nDNS Resolution: True\n\n----------------------\n\n3.0Unclassified5.440IOC004 | Alert – Connectivity FailedtrueLummus Technology Inc1116817180226110003.01Alert: N-Able | Lummus Technology | lum-stbin-pw-01 | Failed Connectivity (#770970)12Alert6.00Alert<span><b>Original title:</b> Failed Connectivity<br>Description: Alert: N-able - Lummus Technology &gt; LUM Azure Production lum-stbin-pw-01 Failed Connectivity <br>Severity: Failed<br>Customer: Lummus Technology &gt; LUM Azure Production<br>Device Name: lum-stbin-pw-01<br>AlertLookup:Connectivity-Failed<br>Device IP: 10.0.16.70<br>Status:<br>URL: <br>Integration Name:<br><br>Alert Code: IOC000 | Connectivity<br><br>Notes:<br>No device note for device lum-stbin-pw-01 <br><br>To remotely access this device, click the following link:<br><br>https://ncod504.n-able.com:443/deepLinkAction.do?method=deviceRC&amp;customerID=224&amp;deviceID=505477052&amp;language=en_US<br><br>Device Property:<br>Device Description: Network device discovered using Asset Discovery - 505477052<br><br>Device Property: Enviroment <br>Device Description: Enviroment Network device discovered using Asset Discovery - 505477052<br><br><br>Issue: At 2024-06-10 08:29:55 the Connectivity - service transitioned from a Normal state to a Failed state.<br><br>Here are the details of the Connectivity - service:<br><br>Packet Loss: 30.00 %<br>Time To Live: 122.00 Hops<br>Average Round Trip Time: 242.00 msec<br>DNS Resolution: True<br><br>----------------------<br><br></span>-74.1812ExactlyIT System Bot2024-06-10 12:35:39lum-stbin-pw-01 (Virtual Compute)2000-01-01 00:00:003873.0IncidentIncident Critical (P1)142640.8410falseFalse{'cisubtype_id_name': '', 'cistage_id_name': 'Production', 'id': 11168, 'citype_id_name': 'Virtual Compute', 'cicriticality_id_name': 'Medium'}https://lummus.exactlyit.com/my/ticket/770970Alert{'team_category': 'Provider', 'id': 373, 'team_level': 'Level 2', 'owner_id_name': 'Gaona, Esaul_EIT | ExactlyIT Inc'}MetSolvedMet01Monitoring Ticket000BloomfieldLevel 20.000.0NaNNaN
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232392024-06-22 15:02:11Ron.Taylor@convergetp.com0.00000042024-06-21 12:34:36False1080.0CEC-Data Center Team000.0, 0.0Taylor, RonCEC5588<p><br></p>Converge TP, Main Location0Converge TPFriday7820872024-06-21 12:34:31[]Web\n\n\n6.0Unclassified0.003trueConverge TP017189732710006.015750CRAC Unit Status Check (#782087)12Incident7.00Phone<p><img class="img-fluid" 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Ron2024-06-22 15:04:462000-01-01 00:00:0031465.0IncidentIncident Low (P4)1293610.0000000falseFalseNaNhttps://exactlyit.com/my/ticket/782087Others{'team_category': 'Provider', 'id': 1080, 'team_level': 'Level 2', 'owner_id_name': 'Slack, Angie | ExactlyIT Inc'}FalseClosedFalse02Service Desk handled010MACONLevel 20.000.0NaNNaN
232402024-06-22 15:23:18Ken.Wong@convergetp.com22.233333222000-01-01 00:00:00Checking ticket on prime time1246.0Converge Internal Help Desk010.0, 0.0Wong, KenMSO5588<p><br></p>Converge TP, Main Location12308Converge TPTuesday7793602024-06-18 16:00:01[[]]Web\n\n\n\nHi,\n\nI’d would like to request for the MS Visio Desktop version to be installed on my PC. Is a corporate license available for use?\n\n \n\nThanks,\n\nKen Wong\n\n| Analytics Architect\n\n\nConverge Technology Solutions    \n\nm 416.529.6255  e ken.wong@convergetp.com    \n\nw convergetp.com    \n\n \n\n \n\n \n\n\n\n7.0Unclassified57.0910CEC-Service Desk-RequesttrueConverge TP1498317187264010009.031338Request: Visio Desktop Installation (#779360)16Service Request4.00Email<p style="margin-bottom: 0px;"><br></p><p style="margin-bottom: 0px;">Hi,</p><p style="margin-bottom: 0px;">I’d would like to request for the MS Visio Desktop version to be installed on my PC. Is a corporate license available for use?</p><p style="margin-bottom: 0px;"> </p><p style="margin-bottom: 0px;">Thanks,</p><p style="margin-bottom: 0px;">Ken Wong</p><p style="margin-bottom: 0px;">| Analytics Architect\n</p><p style="margin-bottom: 0px;">Converge Technology Solutions    </p><p style="margin-bottom: 0px;">m 416.529.6255  e ken.wong@convergetp.com    </p><p style="margin-bottom: 0px;">w convergetp.com    </p><p style="margin-bottom: 0px;"> </p><p style="margin-bottom: 0px;"> </p><p style="margin-bottom: 0px;"> </p><p><br></p>0.000000Escalante, Pedro2024-06-22 14:30:51CEC-Service Desk2024-06-22 15:23:20101953.0Service RequestService Request Normal12293610.0000000false{'cisubtype_id_name': '', 'cistage_id_name': 'Production', 'id': 14983, 'citype_id_name': 'Service', 'cicriticality_id_name': 'Medium'}https://exactlyit.com/my/ticket/779360Others{'team_category': 'Provider', 'id': 1246, 'team_level': 'Level 1', 'owner_id_name': 'Minor, Farah_EIT | ExactlyIT Inc'}RunningWith CustomerMet07Service Desk handledConverge Internal Help Desk060MACONLevel 10.001246.0NaNNaN
232412024-06-22 15:25:47sabrina.Paglia@convergetp.com1.03333372000-01-01 00:00:001246.0Converge Internal Help Desk010.0, 0.0Paglia, SabrinaMSO5588<p><br></p>Converge TP, Main Location12308Converge TPFriday7821992024-06-21 14:21:18[]Web\nHi there,\n\n\nCan you please send me the files that were blocked.  This is a customer and we’re trying to assess payment details.\n\n\nThank you,\n \nSabrina Paglia, CPA/CMA\n|\n\nController, NA \nConverge Technology Solutions    \n \n \nFrom: CTP-Mimecast \n\nSent: Friday, June 21, 2024 10:17 AM\nTo: Sabrina Paglia \nSubject: Files attached to a message triggered a policy\n \n    [EXTERNAL SENDER]\n \n \n \n \nFiles attached to a message triggered a policy\nContact your administrator if you need these files.\n \n \n \nMessage Details\n \nFrom\n"Pina.Pirro@saputo.com" \nTo\nSabrina Paglia \nSubject\nRE: VMware Invoice SAP001 ∙ SAPUTO\nDate\nFri, 21 Jun 2024 14:16:09 +0000\nPolicy\nDefault Suspected Malware Definition, Default Attachment Management Definition - Block Dangerous File Types\nStatus\nThe message has been placed on HOLD - action required\n \n \n \nFile Details\n \n- Attachment Policy (Default Suspected Malware Definition, Default Attachment Management Definition - Block Dangerous File Types)\n\n\nAttachment Name: image009.unpacked_gz\n\nPolicy Name: Default Attachment Management Definition - Block Dangerous File Types\n\nDetected as: wmf\n\nSize: 9052 bytes\n\nAction Taken: Stripped (Blocked)\n\nReason: Not permitted if larger or equal to 0 bytes\n\n\nAttachment Name: image009.unpacked_gz\n\nPolicy Name: Default Suspected Malware Definition\n\nDetected as: wmf\n\nSize: 9052 bytes\n\nAction Taken: HOLD (Entire Message Held for Review)\n\nReason: Dangerous file type found\n \n \n \n \n \n© 2003 - 2019 Mimecast Services Limited.\n \n                                                           \n\n\n\n2.0Unclassified58.5111CEC-Service Desk-RequesttrueConverge TP14983171897967800010.031338FW: Files attached to a message triggered a policy (#782199)14Service Request2.00Email<br>Hi there,<br>\n<br>Can you please send me the files that were blocked.  This is a customer and we’re trying to assess payment details.<br>\n<br>Thank you,<br> <br>Sabrina Paglia, CPA/CMA<br>|\n<br>Controller, NA <br>Converge Technology Solutions    <br> <br> <br>From: CTP-Mimecast \n<br>Sent: Friday, June 21, 2024 10:17 AM<br>To: Sabrina Paglia <br>Subject: Files attached to a message triggered a policy<br> <br>    [EXTERNAL SENDER]<br> <br> <br> <br> <br>Files attached to a message triggered a policy<br>Contact your administrator if you need these files.<br> <br> <br> <br>Message Details<br> <br>From<br>"Pina.Pirro@saputo.com" <br>To<br>Sabrina Paglia <br>Subject<br>RE: VMware Invoice SAP001 ∙ SAPUTO<br>Date<br>Fri, 21 Jun 2024 14:16:09 +0000<br>Policy<br>Default Suspected Malware Definition, Default Attachment Management Definition - Block Dangerous File Types<br>Status<br>The message has been placed on HOLD - action required<br> <br> <br> <br>File Details<br> <br>- Attachment Policy (Default Suspected Malware Definition, Default Attachment Management Definition - Block Dangerous File Types)<br>\n<br>Attachment Name: image009.unpacked_gz\n<br>Policy Name: Default Attachment Management Definition - Block Dangerous File Types\n<br>Detected as: wmf\n<br>Size: 9052 bytes\n<br>Action Taken: Stripped (Blocked)\n<br>Reason: Not permitted if larger or equal to 0 bytes<br>\n<br>Attachment Name: image009.unpacked_gz\n<br>Policy Name: Default Suspected Malware Definition\n<br>Detected as: wmf\n<br>Size: 9052 bytes\n<br>Action Taken: HOLD (Entire Message Held for Review)\n<br>Reason: Dangerous file type found<br> <br> <br> <br> <br> <br>© 2003 - 2019 Mimecast Services Limited.<br> <br>                                                           <br><p><br></p>0.000000Escalante, Pedro2024-06-22 15:25:49CEC-Service Desk2024-06-21 15:23:0773501.0Service RequestService Request Low3293610.0000000falseFalse{'cisubtype_id_name': '', 'cistage_id_name': 'Production', 'id': 14983, 'citype_id_name': 'Service', 'cicriticality_id_name': 'Medium'}https://exactlyit.com/my/ticket/782199Others{'team_category': 'Provider', 'id': 1246, 'team_level': 'Level 1', 'owner_id_name': 'Minor, Farah_EIT | ExactlyIT Inc'}RunningIn ProgressMet03Service Desk handled050MACONLevel 10.000.0NaNNaN
232422024-06-22 15:25:47david.assayag@convergetp.com1.01666772000-01-01 00:00:001084.0CEC-Help Desk010.0, 0.0David AssayagCEC5588<p><br></p>David Assayag12308Converge TPFriday7822012024-06-21 14:24:20[]Web\nHi can you release this email pls\n \nDavid Assayag\n |\nDirecteur de Comptes/Account Executive\nConverge Technology Solutions    \nm \n\n (514)  651 7354\n\ne \ndavid.assayag@convergetp.com\nw \n\nhttps://convergetp.com/\nw \n\nhttps://pcdsolutions.com/\n \n \n \n \nFrom: CTP-Mimecast \n\nSent: Friday, June 21, 2024 10:17 AM\nTo: David Assayag \nSubject: Files attached to a message triggered a policy\n \n    [EXTERNAL SENDER]\n \n \n \n \nFiles attached to a message triggered a policy\nContact your administrator if you need these files.\n \n \n \nMessage Details\n \nFrom\n"Pina.Pirro@saputo.com" \nTo\nDavid Assayag \nSubject\nRE: VMware Invoice SAP001 ∙ SAPUTO\nDate\nFri, 21 Jun 2024 14:16:09 +0000\nPolicy\nDefault Suspected Malware Definition, Default Attachment Management Definition - Block Dangerous File Types\nStatus\nThe message has been placed on HOLD - action required\n \n \n \nFile Details\n \n- Attachment Policy (Default Suspected Malware Definition, Default Attachment Management Definition - Block Dangerous File Types)\n\n\nAttachment Name: image009.unpacked_gz\n\nPolicy Name: Default Attachment Management Definition - Block Dangerous File Types\n\nDetected as: wmf\n\nSize: 9052 bytes\n\nAction Taken: Stripped (Blocked)\n\nReason: Not permitted if larger or equal to 0 bytes\n\n\nAttachment Name: image009.unpacked_gz\n\nPolicy Name: Default Suspected Malware Definition\n\nDetected as: wmf\n\nSize: 9052 bytes\n\nAction Taken: HOLD (Entire Message Held for Review)\n\nReason: Dangerous file type found\n \n \n \n \n \n© 2003 - 2019 Mimecast Services Limited.\n \n                                                           \n\n\n\n2.0Unclassified55.4711CEC-Service Desk-RequesttrueConverge TP14983171897986000010.031338FW: Files attached to a message triggered a policy (#782201)14Service Request2.00Email<br>Hi can you release this email pls<br> <br>David Assayag<br> |<br>Directeur de Comptes/Account Executive<br>Converge Technology Solutions    <br>m \n<br> (514)  651 7354\n<br>e <br>david.assayag@convergetp.com<br>w \n<br>https://convergetp.com/<br>w \n<br>https://pcdsolutions.com/<br> <br> <br> <br> <br>From: CTP-Mimecast \n<br>Sent: Friday, June 21, 2024 10:17 AM<br>To: David Assayag <br>Subject: Files attached to a message triggered a policy<br> <br>    [EXTERNAL SENDER]<br> <br> <br> <br> <br>Files attached to a message triggered a policy<br>Contact your administrator if you need these files.<br> <br> <br> <br>Message Details<br> <br>From<br>"Pina.Pirro@saputo.com" <br>To<br>David Assayag <br>Subject<br>RE: VMware Invoice SAP001 ∙ SAPUTO<br>Date<br>Fri, 21 Jun 2024 14:16:09 +0000<br>Policy<br>Default Suspected Malware Definition, Default Attachment Management Definition - Block Dangerous File Types<br>Status<br>The message has been placed on HOLD - action required<br> <br> <br> <br>File Details<br> <br>- Attachment Policy (Default Suspected Malware Definition, Default Attachment Management Definition - Block Dangerous File Types)<br>\n<br>Attachment Name: image009.unpacked_gz\n<br>Policy Name: Default Attachment Management Definition - Block Dangerous File Types\n<br>Detected as: wmf\n<br>Size: 9052 bytes\n<br>Action Taken: Stripped (Blocked)\n<br>Reason: Not permitted if larger or equal to 0 bytes<br>\n<br>Attachment Name: image009.unpacked_gz\n<br>Policy Name: Default Suspected Malware Definition\n<br>Detected as: wmf\n<br>Size: 9052 bytes\n<br>Action Taken: HOLD (Entire Message Held for Review)\n<br>Reason: Dangerous file type found<br> <br> <br> <br> <br> <br>© 2003 - 2019 Mimecast Services Limited.<br> <br>                                                           <br><p><br></p>0.000000Escalante, Pedro2024-06-22 15:25:49CEC-Service Desk2024-06-21 15:25:3752175.0Service RequestService Request Low3521750.0000000falseFalse{'cisubtype_id_name': '', 'cistage_id_name': 'Production', 'id': 14983, 'citype_id_name': 'Service', 'cicriticality_id_name': 'Medium'}https://exactlyit.com/my/ticket/782201Others{'team_category': 'Provider', 'id': 1084, 'team_level': 'Level 1', 'owner_id_name': 'Minor, Farah_EIT | ExactlyIT Inc'}FalseIn ProgressFalse03Service Desk handled020Level 10.000.0NaNNaN
232432024-06-22 15:22:34Matt.Maetzold@convergetp.com11.500000182000-01-01 00:00:00Checking on prime time1246.0Converge Internal Help Desk010.0, 0.0Maetzold, MattMSO0<p><br></p>Maetzold, Matt0NaNMonday7783312024-06-17 19:40:25[[]]Web\n\nCan you setup mimecast on a tab?\n \n \n \n \nMatthew Maetzold\nManaging Client Director\nConverge Technology Solutions\n_____________\nm: 612.419.1149\nconvergetp.com  |  Matt.Maetzold@convergetp.com\n \n \n\n7.0Unclassified79.5711true0171865322500010.031338question (#778331)19Service Request4.00Email<p style="margin-bottom: 0px;"><br>Can you setup mimecast on a tab?<br> <br> <br> <br> <br>Matthew Maetzold<br>Managing Client Director<br>Converge Technology Solutions<br>_____________<br>m: 612.419.1149<br>convergetp.com  |  Matt.Maetzold@convergetp.com<br> <br> <br></p>0.000000Escalante, Pedro2024-06-22 14:30:502024-06-22 15:22:3545625.0Service RequestService Request Low8456250.0000000falseNaNhttps://exactlyit.com/my/ticket/778331Others{'team_category': 'Provider', 'id': 1246, 'team_level': 'Level 1', 'owner_id_name': 'Minor, Farah_EIT | ExactlyIT Inc'}RunningWith CustomerMet05Service Desk handledConverge Internal Help Desk030Level 10.001246.0NaNNaN
232442024-06-22 15:30:48False1.266667112000-01-01 00:00:001142.0Network Operations Center000.0, 0.0Sun Coast Resources, ITSM MonitoringMSO6177<p><br></p>Sun Coast Resources13374Sun Coast Resources, Inc.Friday7821972024-06-21 14:14:09[[]]Web\n Ticket created from the alert ticket number: 782163\n\n\n\n\nOriginal title: Network Element Offline\nDescription: This network element has gone offline \nSeverity: Emergency \nCustomer: SUN US TX Houston \nURL: https://sunustxhouston.us4.my.auvik.com/alert/1119156528005325257/summary \nEntity name: 6405B_AP-MR84_05 \n\n2.0Unclassified0.002NOC001 | Alert - Auvik - Network Element OfflinetrueSun Coast Resources, Inc.2328317189792490005.031433Follow UP Alert: Auvik | Sun Coast Resources, Inc. | SUN US TX Houston | 6405B_AP-MR84_05 | Network Element Offline (#782197)14Incident2.00Ticket<h2> Ticket created from the alert ticket number: 782163</h2><p style="margin-bottom: 0px;"><br></p><p><b>Original title:</b> Network Element Offline<br><b>Description:</b> This network element has gone offline <br><b>Severity:</b> Emergency <br><b>Customer:</b> SUN US TX Houston <br><b>URL:</b> <a href="https://sunustxhouston.us4.my.auvik.com/alert/1119156528005325257/summary" target="_blank">https://sunustxhouston.us4.my.auvik.com/alert/1119156528005325257/summary</a> <br><b>Entity name:</b> 6405B_AP-MR84_05 <br></p>0.000000Aguilar, David_EIT2024-06-22 15:30:496405B_AP-MR84_052024-06-21 15:30:4937343.0IncidentIncident Normal (P3)3373190.0000000false{'cisubtype_id_name': 'WAP', 'cistage_id_name': 'Production', 'id': 23283, 'citype_id_name': 'Network', 'cicriticality_id_name': 'Medium'}https://exactlyit.com/my/ticket/782197Others{'team_category': 'Provider', 'id': 1142, 'team_level': 'Level 1', 'owner_id_name': 'Pena, Rafael_EIT | ExactlyIT Inc'}RunningIn ProgressMet02Service Desk handledNetwork Operations Center020HoustonLevel 10.921142.0NaNNaN
232452024-06-22 15:43:161@1.com0.583333762024-06-22 15:43:16False373.0EIT-Infrastructure Operations Center0700.0, 0.0Sekisui Specialty Chemicals America, LLC (Converge) ITSM MonitoringMSO7069Sekisui Specialty Chemicals America, LLC (Converge) ITSM Monitoring12547Sekisui Specialty Chemicals America LLCFriday7826292024-06-21 23:47:31[]WebOriginal title: Failed Agent Status\nDescription: Alert: N-able - Sekisui Specialty Chemicals America, LLC > SEK US TX Allen GDCSQL Failed Agent Status \nSeverity: Failed\nCustomer: Sekisui Specialty Chemicals America, LLC > SEK US TX Allen\nDevice Name: GDCSQL\nAlertLookup:Agent Status-Failed\nDevice IP: 10.72.52.29\nStatus:\nURL: \nIntegration Name:\n\nAlert Code: IOC000 | Agent Status\n\nNotes:\nNo device note for device GDCSQL \n\nTo remotely access this device, click the following link:\n\nhttps://ncod504.n-able.com:443/deepLinkAction.do?method=deviceRC&customerID=1993&deviceID=318841658&language=en_US\n\nDevice Property:\nDevice Description: Network device discovered using Asset Discovery - 318841658\n\nDevice Property: Enviroment \nDevice Description: Enviroment Network device discovered using Asset Discovery - 318841658\n\n\nIssue: At 2024-06-21 19:47:18 the Agent Status - service transitioned from a Normal state to a Failed state.\n\nHere are the details of the Agent Status - service:\n\nAgent check-in interval: 56.78 min\n\n----------------------\n\n3.0Unclassified0.000IOC001 | Alert - Windows Agent StatustrueSekisui Specialty Chemicals America LLC2082817190136510003.01Alert: N-Able | Sekisui Specialty Chemicals America, LLC | GDCSQL | Failed Agent Status (#782629)23Alert6.00Alert<span><b>Original title:</b> Failed Agent Status<br>Description: Alert: N-able - Sekisui Specialty Chemicals America, LLC &gt; SEK US TX Allen GDCSQL Failed Agent Status <br>Severity: Failed<br>Customer: Sekisui Specialty Chemicals America, LLC &gt; SEK US TX Allen<br>Device Name: GDCSQL<br>AlertLookup:Agent Status-Failed<br>Device IP: 10.72.52.29<br>Status:<br>URL: <br>Integration Name:<br><br>Alert Code: IOC000 | Agent Status<br><br>Notes:<br>No device note for device GDCSQL <br><br>To remotely access this device, click the following link:<br><br>https://ncod504.n-able.com:443/deepLinkAction.do?method=deviceRC&amp;customerID=1993&amp;deviceID=318841658&amp;language=en_US<br><br>Device Property:<br>Device Description: Network device discovered using Asset Discovery - 318841658<br><br>Device Property: Enviroment <br>Device Description: Enviroment Network device discovered using Asset Discovery - 318841658<br><br><br>Issue: At 2024-06-21 19:47:18 the Agent Status - service transitioned from a Normal state to a Failed state.<br><br>Here are the details of the Agent Status - service:<br><br>Agent check-in interval: 56.78 min<br><br>----------------------<br><br></span>0.000000ExactlyIT System Bot2024-06-22 15:43:17GDCSQL2024-06-22 13:42:0750491.0IncidentIncident Critical (P1)70504910.0000000falseFalse{'cisubtype_id_name': '', 'cistage_id_name': 'Production', 'id': 20828, 'citype_id_name': 'Virtual Compute', 'cicriticality_id_name': 'High'}https://exactlyit.com/my/ticket/782629Alert{'team_category': 'Provider', 'id': 373, 'team_level': 'Level 2', 'owner_id_name': 'Gaona, Esaul_EIT | ExactlyIT Inc'}MetSolvedMet04Monitoring Ticket000DallasLevel 20.330.0NaNNaN
232462024-06-22 15:43:45False0.0000001302024-06-22 15:43:45False373.0EIT-Infrastructure Operations Center0910.0, 0.0Tom Barrow Company ITSM MonitoringMSO8998<p><br></p>Tom Barrow Company ITSM12552Tom Barrow CompanySaturday7826402024-06-22 00:10:02[]Web\nOriginal title: Failed Connectivity\nDescription: Alert: N-able - Tom Barrow > TOM General TBCSAV1 Failed Connectivity \nSeverity: Failed\nCustomer: Tom Barrow > TOM General\nDevice Name: TBCSAV1\nAlertLookup:Connectivity-Failed\nDevice IP: 192.168.9.18\nStatus:\nURL: \nIntegration Name:\n\nAlert Code: IOC000 | Connectivity\n\nNotes:\nNo device note for device TBCSAV1 \n\nTo remotely access this device, click the following link:\n\nhttps://ncod504.n-able.com:443/deepLinkAction.do?method=deviceRC&customerID=2060&deviceID=1476467970&language=en_US\n\nDevice Property:\nDevice Description: Network device discovered using Asset Discovery - 1476467970\n\nDevice Property: Enviroment \nDevice Description: Enviroment Network device discovered using Asset Discovery - 1476467970\n\n\nIssue: At 2024-06-21 20:09:42 the Connectivity - service transitioned from a Normal state to a Failed state.\n\nHere are the details of the Connectivity - service:\n\nPacket Loss: 30.00 %\nTime To Live: 124.00 Hops\nAverage Round Trip Time: 195.00 msec\nDNS Resolution: True\n\n----------------------\n\n\n3.0False positive0.002IOC004 | Alert – Connectivity FailedtrueTom Barrow Company017190150020005.01Alert: N-Able | Tom Barrow | TBCSAV1 | Failed Connectivity (#782640)0Alert6.00Alert<p style="margin-bottom: 0px;"><b>Original title:</b> Failed Connectivity<br>Description: Alert: N-able - Tom Barrow &gt; TOM General TBCSAV1 Failed Connectivity <br>Severity: Failed<br>Customer: Tom Barrow &gt; TOM General<br>Device Name: TBCSAV1<br>AlertLookup:Connectivity-Failed<br>Device IP: 192.168.9.18<br>Status:<br>URL: <br>Integration Name:<br><br>Alert Code: IOC000 | Connectivity<br><br>Notes:<br>No device note for device TBCSAV1 <br><br>To remotely access this device, click the following link:<br><br>https://ncod504.n-able.com:443/deepLinkAction.do?method=deviceRC&amp;customerID=2060&amp;deviceID=1476467970&amp;language=en_US<br><br>Device Property:<br>Device Description: Network device discovered using Asset Discovery - 1476467970<br><br>Device Property: Enviroment <br>Device Description: Enviroment Network device discovered using Asset Discovery - 1476467970<br><br><br>Issue: At 2024-06-21 20:09:42 the Connectivity - service transitioned from a Normal state to a Failed state.<br><br>Here are the details of the Connectivity - service:<br><br>Packet Loss: 30.00 %<br>Time To Live: 124.00 Hops<br>Average Round Trip Time: 195.00 msec<br>DNS Resolution: True<br><br>----------------------<br><br></p>0.000000ExactlyIT System Bot2024-06-22 15:43:452024-06-22 15:34:5774661.0IncidentIncident Normal (P3)98746580.0000000falseFalseNaNhttps://exactlyit.com/my/ticket/782640Alert{'team_category': 'Provider', 'id': 373, 'team_level': 'Level 2', 'owner_id_name': 'Gaona, Esaul_EIT | ExactlyIT Inc'}MetSolvedMet06Monitoring Ticket000AtlantaLevel 20.830.0NaNNaN
232472024-06-22 15:48:05False0.883333482000-01-01 00:00:00False373.0EIT-Infrastructure Operations Center0360.0, 0.0Tom Barrow Company ITSM MonitoringMSO8998<p><br></p>Tom Barrow Company ITSM12552Tom Barrow CompanyFriday7826352024-06-21 23:59:03[]Web\nOriginal title: Failed Connectivity\nDescription: Alert: N-able - Tom Barrow > TOM General TBCORLANDO2 Failed Connectivity \nSeverity: Failed\nCustomer: Tom Barrow > TOM General\nDevice Name: TBCORLANDO2\nAlertLookup:Connectivity-Failed\nDevice IP: 192.168.4.16\nStatus:\nURL: \nIntegration Name:\n\nAlert Code: IOC000 | Connectivity\n\nNotes:\nNo device note for device TBCORLANDO2 \n\nTo remotely access this device, click the following link:\n\nhttps://ncod504.n-able.com:443/deepLinkAction.do?method=deviceRC&customerID=2060&deviceID=203683526&language=en_US\n\nDevice Property:\nDevice Description: Network device discovered using Asset Discovery - 203683526\n\nDevice Property: Enviroment \nDevice Description: Enviroment Network device discovered using Asset Discovery - 203683526\n\n\nIssue: At 2024-06-21 19:58:27 the Connectivity - service transitioned from a Warning state to a Failed state.\n\nHere are the details of the Connectivity - service:\n\nPacket Loss: 10.00 %\nTime To Live: 124.00 Hops\nAverage Round Trip Time: 430.00 msec\nDNS Resolution: True\n\n----------------------\n\n\n2.0False positive0.000IOC004 | Alert – Connectivity FailedtrueTom Barrow Company017190143430003.021991Alert: N-Able | Tom Barrow | TBCORLANDO2 | Failed Connectivity (#782635)23Alert2.00Alert<p style="margin-bottom: 0px;"><b>Original title:</b> Failed Connectivity<br>Description: Alert: N-able - Tom Barrow &gt; TOM General TBCORLANDO2 Failed Connectivity <br>Severity: Failed<br>Customer: Tom Barrow &gt; TOM General<br>Device Name: TBCORLANDO2<br>AlertLookup:Connectivity-Failed<br>Device IP: 192.168.4.16<br>Status:<br>URL: <br>Integration Name:<br><br>Alert Code: IOC000 | Connectivity<br><br>Notes:<br>No device note for device TBCORLANDO2 <br><br>To remotely access this device, click the following link:<br><br>https://ncod504.n-able.com:443/deepLinkAction.do?method=deviceRC&amp;customerID=2060&amp;deviceID=203683526&amp;language=en_US<br><br>Device Property:<br>Device Description: Network device discovered using Asset Discovery - 203683526<br><br>Device Property: Enviroment <br>Device Description: Enviroment Network device discovered using Asset Discovery - 203683526<br><br><br>Issue: At 2024-06-21 19:58:27 the Connectivity - service transitioned from a Warning state to a Failed state.<br><br>Here are the details of the Connectivity - service:<br><br>Packet Loss: 10.00 %<br>Time To Live: 124.00 Hops<br>Average Round Trip Time: 430.00 msec<br>DNS Resolution: True<br><br>----------------------<br><br></p>0.000000Rosas, Manuel_EIT2024-06-22 15:43:472024-06-22 15:48:0774661.0IncidentIncident Critical (P1)38746580.0000000falseFalseNaNhttps://exactlyit.com/my/ticket/782635Alert{'team_category': 'Provider', 'id': 373, 'team_level': 'Level 2', 'owner_id_name': 'Gaona, Esaul_EIT | ExactlyIT Inc'}RunningIn ProgressMet05Monitoring Ticket000AtlantaLevel 20.500.0NaNNaN
232482024-06-22 15:49:14False0.66666782024-06-22 15:49:14False373.0EIT-Infrastructure Operations Center0629.7462013, -95.55963059999999LiquidPower Specialty Products Inc., IT Monitoring EventsMSO92<p><br></p>LSPI ITSM12551LiquidPower Specialty Products Inc.Saturday7827012024-06-22 02:37:01[]Web\nOriginal title: Failed CPU\nDescription: Alert: N-able - LiquidPower Specialty Products Inc. > LIQ US TX Bryan BRYVMPMSTN2A Failed CPU \nSeverity: Failed\nCustomer: LiquidPower Specialty Products Inc. > LIQ US TX Bryan\nDevice Name: BRYVMPMSTN2A\nAlertLookup:CPU-Failed\nDevice IP: 192.168.10.12\nStatus:\nURL: \nIntegration Name:\n\nAlert Code: IOC000 | CPU\n\nNotes:\nDevice Notes: \n\nNote created on 6/6/24, 4:37 PMBy: Manuel.Rosas.ADM@convergetp.com: \nA follow up process was performed without success, the app Owner: Paskos, Jennie didn't approved o replied to increase the storage in the device's disk F, review the ticket: Follow UP Alert: N-Able | LiquidPower Specialty Products Inc. | HSNVMPVEEAM01 | Warning Disk (#757776).\n \n\nTo remotely access this device, click the following link:\n\nhttps://ncod504.n-able.com:443/deepLinkAction.do?method=deviceRC&customerID=1343&deviceID=1725619351&language=en_US\n\nDevice Property:\nDevice Description: Network device discovered using Asset Discovery - 1725619351\n\nDevice Property: Enviroment \nDevice Description: Enviroment Network device discovered using Asset Discovery - 1725619351\n\n\nIssue: At 2024-06-21 22:36:28 the CPU - service transitioned from a Normal state to a Failed state.\n\nHere are the details of the CPU - service:\n\nCPU Usage: 95.00 %\nTop Process 1: VideoOS.Recorder.Service\nTop Process 2: MsMpEng\nTop Process 3: svchost\nTop Process 4: System\nTop Process 5: ProxySrv\nPID of Process 1: 2448\nPID of Process 2: 3720\nPID of Process 3: 25776\nPID of Process 4: 4\nPID of Process 5: 10932\nUser of Process 1: NT AUTHORITY\NETWORK SERVICE\nUser of Process 2: NT AUTHORITY\SYSTEM\nUser of Process 3: NT AUTHORITY\SYSTEM\nUser of Process 4: NT AUTHORITY\SYSTEM\nUser of Process 5: NT AUTHORITY\NETWORK SERVICE\nCPU Usage for Process 1: 60.00 %\nCPU Usage for Process 2: 10.00 %\nCPU Usage for Process 3: 9.00 %\nCPU Usage for Process 4: 2.00 %\nCPU Usage for Process 5: 2.00 %\n\n----------------------\n\n\n3.0False positive0.001IOC003 | Failed CPUtrueLiquidPower Specialty Products Inc.1721017190238210004.01Alert: N-Able | LiquidPower Specialty Products Inc. | BRYVMPMSTN2A | Failed CPU (#782701)2Alert6.00Alert<p style="margin-bottom: 0px;"><b>Original title:</b> Failed CPU<br>Description: Alert: N-able - LiquidPower Specialty Products Inc. &gt; LIQ US TX Bryan BRYVMPMSTN2A Failed CPU <br>Severity: Failed<br>Customer: LiquidPower Specialty Products Inc. &gt; LIQ US TX Bryan<br>Device Name: BRYVMPMSTN2A<br>AlertLookup:CPU-Failed<br>Device IP: 192.168.10.12<br>Status:<br>URL: <br>Integration Name:<br><br>Alert Code: IOC000 | CPU<br><br>Notes:<br>Device Notes: <br><br>Note created on 6/6/24, 4:37 PMBy: Manuel.Rosas.ADM@convergetp.com: <br>A follow up process was performed without success, the app Owner: Paskos, Jennie didn't approved o replied to increase the storage in the device's disk F, review the ticket: Follow UP Alert: N-Able | LiquidPower Specialty Products Inc. | HSNVMPVEEAM01 | Warning Disk (#757776).<br> <br><br>To remotely access this device, click the following link:<br><br>https://ncod504.n-able.com:443/deepLinkAction.do?method=deviceRC&amp;customerID=1343&amp;deviceID=1725619351&amp;language=en_US<br><br>Device Property:<br>Device Description: Network device discovered using Asset Discovery - 1725619351<br><br>Device Property: Enviroment <br>Device Description: Enviroment Network device discovered using Asset Discovery - 1725619351<br><br><br>Issue: At 2024-06-21 22:36:28 the CPU - service transitioned from a Normal state to a Failed state.<br><br>Here are the details of the CPU - service:<br><br>CPU Usage: 95.00 %<br>Top Process 1: VideoOS.Recorder.Service<br>Top Process 2: MsMpEng<br>Top Process 3: svchost<br>Top Process 4: System<br>Top Process 5: ProxySrv<br>PID of Process 1: 2448<br>PID of Process 2: 3720<br>PID of Process 3: 25776<br>PID of Process 4: 4<br>PID of Process 5: 10932<br>User of Process 1: NT AUTHORITY\NETWORK SERVICE<br>User of Process 2: NT AUTHORITY\SYSTEM<br>User of Process 3: NT AUTHORITY\SYSTEM<br>User of Process 4: NT AUTHORITY\SYSTEM<br>User of Process 5: NT AUTHORITY\NETWORK SERVICE<br>CPU Usage for Process 1: 60.00 %<br>CPU Usage for Process 2: 10.00 %<br>CPU Usage for Process 3: 9.00 %<br>CPU Usage for Process 4: 2.00 %<br>CPU Usage for Process 5: 2.00 %<br><br>----------------------<br><br></p>-95.559631ExactlyIT System Bot2024-06-22 15:49:16BRYVMPMSTN2A2024-06-22 15:40:416298.0IncidentIncident High (P2)6599529.7462010falseFalse{'cisubtype_id_name': 'Virtual', 'cistage_id_name': 'Production', 'id': 17210, 'citype_id_name': 'Virtual Compute', 'cicriticality_id_name': 'High'}https://exactlyit.com/my/ticket/782701Alert{'team_category': 'Provider', 'id': 373, 'team_level': 'Level 2', 'owner_id_name': 'Gaona, Esaul_EIT | ExactlyIT Inc'}MetSolvedMet02Monitoring Ticket000HoustonLevel 20.170.0NaNNaN